Upload folder using huggingface_hub

README.md

@@ -1,21 +1,63 @@
 ---
 base_model: unsloth/gemma-4-e2b-it-unsloth-bnb-4bit
+library_name: peft
+model_name: unsloth_gemma-4-E2B-it_1780218767
 tags:
-- text-generation-inference
+- base_model:adapter:unsloth/gemma-4-e2b-it-unsloth-bnb-4bit
+- lora
+- sft
 - transformers
+- trl
 - unsloth
-- gemma4
-license: apache-2.0
-language:
-- en
+licence: license
+pipeline_tag: text-generation
 ---
 
-# Uploaded finetuned  model
+# Model Card for unsloth_gemma-4-E2B-it_1780218767
 
-- **Developed by:** prog-love
-- **License:** apache-2.0
-- **Finetuned from model :** unsloth/gemma-4-e2b-it-unsloth-bnb-4bit
+This model is a fine-tuned version of [unsloth/gemma-4-e2b-it-unsloth-bnb-4bit](https://huggingface.co/unsloth/gemma-4-e2b-it-unsloth-bnb-4bit).
+It has been trained using [TRL](https://github.com/huggingface/trl).
 
-This gemma4 model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
+## Quick start
 
-[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)
+```python
+from transformers import pipeline
+
+question = "If you had a time machine, but could only go to the past or the future once and never return, which would you choose and why?"
+generator = pipeline("text-generation", model="None", device="cuda")
+output = generator([{"role": "user", "content": question}], max_new_tokens=128, return_full_text=False)[0]
+print(output["generated_text"])
+```
+
+## Training procedure
+
+ 
+
+
+This model was trained with SFT.
+
+### Framework versions
+
+- PEFT 0.18.1
+- TRL: 0.23.1
+- Transformers: 5.5.0
+- Pytorch: 2.10.0+cu128
+- Datasets: 4.3.0
+- Tokenizers: 0.22.2
+
+## Citations
+
+
+
+Cite TRL as:
+    
+```bibtex
+@misc{vonwerra2022trl,
+	title        = {{TRL: Transformer Reinforcement Learning}},
+	author       = {Leandro von Werra and Younes Belkada and Lewis Tunstall and Edward Beeching and Tristan Thrush and Nathan Lambert and Shengyi Huang and Kashif Rasul and Quentin Gallou{\'e}dec},
+	year         = 2020,
+	journal      = {GitHub repository},
+	publisher    = {GitHub},
+	howpublished = {\url{https://github.com/huggingface/trl}}
+}
+```

adapter_config.json

@@ -0,0 +1,51 @@
+{
+  "alora_invocation_tokens": null,
+  "alpha_pattern": {},
+  "arrow_config": null,
+  "auto_mapping": {
+    "base_model_class": "Gemma4ForConditionalGeneration",
+    "parent_library": "transformers.models.gemma4.modeling_gemma4",
+    "unsloth_fixed": true
+  },
+  "base_model_name_or_path": "unsloth/gemma-4-e2b-it-unsloth-bnb-4bit",
+  "bias": "none",
+  "corda_config": null,
+  "ensure_weight_tying": false,
+  "eva_config": null,
+  "exclude_modules": null,
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layer_replication": null,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 32,
+  "lora_bias": false,
+  "lora_dropout": 0.0,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "peft_version": "0.18.1",
+  "qalora_group_size": 16,
+  "r": 16,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "q_proj",
+    "gate_proj",
+    "v_proj",
+    "k_proj",
+    "down_proj",
+    "o_proj",
+    "up_proj"
+  ],
+  "target_parameters": null,
+  "task_type": "CAUSAL_LM",
+  "trainable_token_indices": null,
+  "use_dora": false,
+  "use_qalora": false,
+  "use_rslora": false,
+  "unsloth_training_method": "qlora"
+}

adapter_model.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:dae7c101be06c818341a1b3354a5715c93ad40fc4c4700a81f0c71c0e699b82b
+size 124277728

checkpoint-120/README.md

@@ -0,0 +1,210 @@
+---
+base_model: unsloth/gemma-4-e2b-it-unsloth-bnb-4bit
+library_name: peft
+pipeline_tag: text-generation
+tags:
+- base_model:adapter:unsloth/gemma-4-e2b-it-unsloth-bnb-4bit
+- lora
+- sft
+- transformers
+- trl
+- unsloth
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **Developed by:** [More Information Needed]
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed]
+- **Finetuned from model [optional]:** [More Information Needed]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[More Information Needed]
+
+### Downstream Use [optional]
+
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+
+[More Information Needed]
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+[More Information Needed]
+
+## Training Details
+
+### Training Data
+
+<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+
+[More Information Needed]
+
+### Training Procedure
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
+- **Compute Region:** [More Information Needed]
+- **Carbon Emitted:** [More Information Needed]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]
+### Framework versions
+
+- PEFT 0.18.1

checkpoint-120/adapter_config.json

@@ -0,0 +1,50 @@
+{
+  "alora_invocation_tokens": null,
+  "alpha_pattern": {},
+  "arrow_config": null,
+  "auto_mapping": {
+    "base_model_class": "Gemma4ForConditionalGeneration",
+    "parent_library": "transformers.models.gemma4.modeling_gemma4",
+    "unsloth_fixed": true
+  },
+  "base_model_name_or_path": "unsloth/gemma-4-e2b-it-unsloth-bnb-4bit",
+  "bias": "none",
+  "corda_config": null,
+  "ensure_weight_tying": false,
+  "eva_config": null,
+  "exclude_modules": null,
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layer_replication": null,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 32,
+  "lora_bias": false,
+  "lora_dropout": 0.0,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "peft_version": "0.18.1",
+  "qalora_group_size": 16,
+  "r": 16,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "q_proj",
+    "gate_proj",
+    "v_proj",
+    "k_proj",
+    "down_proj",
+    "o_proj",
+    "up_proj"
+  ],
+  "target_parameters": null,
+  "task_type": "CAUSAL_LM",
+  "trainable_token_indices": null,
+  "use_dora": false,
+  "use_qalora": false,
+  "use_rslora": false
+}

checkpoint-120/adapter_model.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:a2fa7f51110b2c95c35000062cb6a564c25910d5c3d47a3ab9455def2a9d031c
+size 124277728

checkpoint-120/chat_template.jinja

@@ -0,0 +1,351 @@
+{%- macro format_parameters(properties, required, filter_keys=false) -%}
+    {%- set standard_keys = ['description', 'type', 'properties', 'required', 'nullable'] -%}
+    {%- set ns = namespace(found_first=false) -%}
+    {%- for key, value in properties | dictsort -%}
+        {%- set add_comma = false -%}
+        {%- if not filter_keys or key not in standard_keys -%}
+            {%- if ns.found_first %},{% endif -%}
+            {%- set ns.found_first = true -%}
+            {{ key }}:{
+            {%- if value['description'] -%}
+                description:<|"|>{{ value['description'] }}<|"|>
+                {%- set add_comma = true -%}
+            {%- endif -%}
+            {%- if value['type'] | upper == 'STRING' -%}
+                {%- if value['enum'] -%}
+                    {%- if add_comma %},{%- else -%} {%- set add_comma = true -%} {% endif -%}
+                    enum:{{ format_argument(value['enum']) }}
+                {%- endif -%}
+            {%- elif value['type'] | upper == 'ARRAY' -%}
+                {%- if value['items'] is mapping and value['items'] -%}
+                    {%- if add_comma %},{%- else -%} {%- set add_comma = true -%} {% endif -%}
+                    items:{
+                    {%- set ns_items = namespace(found_first=false) -%}
+                    {%- for item_key, item_value in value['items'] | dictsort -%}
+                        {%- if item_value is not none -%}
+                            {%- if ns_items.found_first %},{% endif -%}
+                            {%- set ns_items.found_first = true -%}
+                            {%- if item_key == 'properties' -%}
+                                properties:{
+                                {%- if item_value is mapping -%}
+                                    {{- format_parameters(item_value, value['items']['required'] | default([])) -}}
+                                {%- endif -%}
+                                }
+                            {%- elif item_key == 'required' -%}
+                                required:[
+                                {%- for req_item in item_value -%}
+                                    <|"|>{{- req_item -}}<|"|>
+                                    {%- if not loop.last %},{% endif -%}
+                                {%- endfor -%}
+                                ]
+                            {%- elif item_key == 'type' -%}
+                                {%- if item_value is string -%}
+                                    type:{{ format_argument(item_value | upper) }}
+                                {%- else -%}
+                                    type:{{ format_argument(item_value | map('upper') | list) }}
+                                {%- endif -%}
+                            {%- else -%}
+                                {{ item_key }}:{{ format_argument(item_value) }}
+                            {%- endif -%}
+                        {%- endif -%}
+                    {%- endfor -%}
+                    }
+                {%- endif -%}
+            {%- endif -%}
+            {%- if value['nullable'] %}
+                {%- if add_comma %},{%- else -%} {%- set add_comma = true -%} {% endif -%}
+                nullable:true
+            {%- endif -%}
+            {%- if value['type'] | upper == 'OBJECT' -%}
+                {%- if value['properties'] is defined and value['properties'] is mapping -%}
+                    {%- if add_comma %},{%- else -%} {%- set add_comma = true -%} {% endif -%}
+                    properties:{
+                    {{- format_parameters(value['properties'], value['required'] | default([])) -}}
+                    }
+                {%- elif value is mapping -%}
+                    {%- if add_comma %},{%- else -%} {%- set add_comma = true -%} {% endif -%}
+                    properties:{
+                    {{- format_parameters(value, value['required'] | default([]), filter_keys=true) -}}
+                    }
+                {%- endif -%}
+                {%- if value['required'] -%}
+                    {%- if add_comma %},{%- else -%} {%- set add_comma = true -%} {% endif -%}
+                    required:[
+                    {%- for item in value['required'] | default([]) -%}
+                        <|"|>{{- item -}}<|"|>
+                        {%- if not loop.last %},{% endif -%}
+                    {%- endfor -%}
+                    ]
+                {%- endif -%}
+            {%- endif -%}
+            {%- if add_comma %},{%- else -%} {%- set add_comma = true -%} {% endif -%}
+            type:<|"|>{{ value['type'] | upper }}<|"|>}
+        {%- endif -%}
+    {%- endfor -%}
+{%- endmacro -%}
+{%- macro format_function_declaration(tool_data) -%}
+    declaration:{{- tool_data['function']['name'] -}}{description:<|"|>{{- tool_data['function']['description'] -}}<|"|>
+    {%- set params = tool_data['function']['parameters'] -%}
+    {%- if params -%}
+        ,parameters:{
+        {%- if params['properties'] -%}
+            properties:{ {{- format_parameters(params['properties'], params['required']) -}} },
+        {%- endif -%}
+        {%- if params['required'] -%}
+            required:[
+            {%- for item in params['required'] -%}
+                <|"|>{{- item -}}<|"|>
+                {{- ',' if not loop.last -}}
+            {%- endfor -%}
+            ],
+        {%- endif -%}
+        {%- if params['type'] -%}
+            type:<|"|>{{- params['type'] | upper -}}<|"|>}
+        {%- endif -%}
+    {%- endif -%}
+    {%- if 'response' in tool_data['function'] -%}
+        {%- set response_declaration = tool_data['function']['response'] -%}
+        ,response:{
+        {%- if response_declaration['description'] -%}
+            description:<|"|>{{- response_declaration['description'] -}}<|"|>,
+        {%- endif -%}
+        {%- if response_declaration['type'] | upper == 'OBJECT' -%}
+            type:<|"|>{{- response_declaration['type'] | upper -}}<|"|>}
+        {%- endif -%}
+    {%- endif -%}
+    }
+{%- endmacro -%}
+{%- macro format_argument(argument, escape_keys=True) -%}
+    {%- if argument is string -%}
+        {{- '<|"|>' + argument + '<|"|>' -}}
+    {%- elif argument is boolean -%}
+        {{- 'true' if argument else 'false' -}}
+    {%- elif argument is mapping -%}
+        {{- '{' -}}
+        {%- set ns = namespace(found_first=false) -%}
+        {%- for key, value in argument | dictsort -%}
+            {%- if ns.found_first %},{% endif -%}
+            {%- set ns.found_first = true -%}
+            {%- if escape_keys -%}
+                {{- '<|"|>' + key + '<|"|>' -}}
+            {%- else -%}
+                {{- key -}}
+            {%- endif -%}
+            :{{- format_argument(value, escape_keys=escape_keys) -}}
+        {%- endfor -%}
+        {{- '}' -}}
+    {%- elif argument is sequence -%}
+        {{- '[' -}}
+        {%- for item in argument -%}
+            {{- format_argument(item, escape_keys=escape_keys) -}}
+            {%- if not loop.last %},{% endif -%}
+        {%- endfor -%}
+        {{- ']' -}}
+    {%- else -%}
+        {{- argument -}}
+    {%- endif -%}
+{%- endmacro -%}
+{%- macro strip_thinking(text) -%}
+    {%- set ns = namespace(result='') -%}
+    {%- for part in text.split('<channel|>') -%}
+        {%- if '<|channel>' in part -%}
+            {%- set ns.result = ns.result + part.split('<|channel>')[0] -%}
+        {%- else -%}
+            {%- set ns.result = ns.result + part -%}
+        {%- endif -%}
+    {%- endfor -%}
+    {{- ns.result | trim -}}
+{%- endmacro -%}
+
+{%- macro format_tool_response_block(tool_name, response) -%}
+    {{- '<|tool_response>' -}}
+    {%- if response is mapping -%}
+        {{- 'response:' + tool_name + '{' -}}
+        {%- for key, value in response | dictsort -%}
+            {{- key -}}:{{- format_argument(value, escape_keys=False) -}}
+            {%- if not loop.last %},{% endif -%}
+        {%- endfor -%}
+        {{- '}' -}}
+    {%- else -%}
+        {{- 'response:' + tool_name + '{value:' + format_argument(response, escape_keys=False) + '}' -}}
+    {%- endif -%}
+    {{- '<tool_response|>' -}}
+{%- endmacro -%}
+
+{%- set ns = namespace(prev_message_type=None) -%}
+{%- set loop_messages = messages -%}
+{{- bos_token -}}
+{#- Handle System/Tool Definitions Block -#}
+{%- if (enable_thinking is defined and enable_thinking) or tools or messages[0]['role'] in ['system', 'developer'] -%}
+    {{- '<|turn>system\n' -}}
+    {#- Inject Thinking token at the very top of the FIRST system turn -#}
+    {%- if enable_thinking is defined and enable_thinking -%}
+        {{- '<|think|>\n' -}}
+        {%- set ns.prev_message_type = 'think' -%}
+    {%- endif -%}
+    {%- if messages[0]['role'] in ['system', 'developer'] -%}
+        {%- if messages[0]['content'] is string -%}
+            {{- messages[0]['content'] | trim -}}
+        {%- elif messages[0]['content'] is sequence -%}
+            {%- for item in messages[0]['content'] -%}
+                {{- item['text'] | trim + ' '-}}
+            {%- endfor -%}
+        {%- endif -%}
+        {%- set loop_messages = messages[1:] -%}
+    {%- endif -%}
+    {%- if tools -%}
+        {%- for tool in tools %}
+            {{- '<|tool>' -}}
+            {{- format_function_declaration(tool) | trim -}}
+            {{- '<tool|>' -}}
+        {%- endfor %}
+        {%- set ns.prev_message_type = 'tool' -%}
+    {%- endif -%}
+    {{- '<turn|>\n' -}}
+{%- endif %}
+
+{#- Pre-scan: find last user message index for reasoning guard -#}
+{%- set ns_turn = namespace(last_user_idx=-1) -%}
+{%- for i in range(loop_messages | length) -%}
+    {%- if loop_messages[i]['role'] == 'user' -%}
+        {%- set ns_turn.last_user_idx = i -%}
+    {%- endif -%}
+{%- endfor -%}
+
+{#- Loop through messages -#}
+{%- for message in loop_messages -%}
+    {%- if message['role'] != 'tool' -%}
+    {%- set ns.prev_message_type = None -%}
+    {%- set role = 'model' if message['role'] == 'assistant' else message['role'] -%}
+    {#- Detect continuation: suppress duplicate <|turn>model when previous non-tool message was also assistant -#}
+    {%- set prev_nt = namespace(role=None, found=false) -%}
+    {%- if loop.index0 > 0 -%}
+        {%- for j in range(loop.index0 - 1, -1, -1) -%}
+            {%- if not prev_nt.found -%}
+                {%- if loop_messages[j]['role'] != 'tool' -%}
+                    {%- set prev_nt.role = loop_messages[j]['role'] -%}
+                    {%- set prev_nt.found = true -%}
+                {%- endif -%}
+            {%- endif -%}
+        {%- endfor -%}
+    {%- endif -%}
+    {%- set continue_same_model_turn = (role == 'model' and prev_nt.role == 'assistant') -%}
+    {%- if not continue_same_model_turn -%}
+        {{- '<|turn>' + role + '\n' }}
+    {%- endif -%}
+
+    {#- Render reasoning/reasoning_content as thinking channel -#}
+    {%- set thinking_text = message.get('reasoning') or message.get('reasoning_content') -%}
+    {%- if thinking_text and loop.index0 > ns_turn.last_user_idx and message.get('tool_calls') -%}
+        {{- '<|channel>thought\n' + thinking_text + '\n<channel|>' -}}
+    {%- endif -%}
+
+            {%- if message['tool_calls'] -%}
+                {%- for tool_call in message['tool_calls'] -%}
+                    {%- set function = tool_call['function'] -%}
+                    {{- '<|tool_call>call:' + function['name'] + '{' -}}
+                    {%- if function['arguments'] is mapping -%}
+                        {%- set ns_args = namespace(found_first=false) -%}
+                        {%- for key, value in function['arguments'] | dictsort -%}
+                            {%- if ns_args.found_first %},{% endif -%}
+                            {%- set ns_args.found_first = true -%}
+                            {{- key -}}:{{- format_argument(value, escape_keys=False) -}}
+                        {%- endfor -%}
+                    {%- elif function['arguments'] is string -%}
+                        {{- function['arguments'] -}}
+                    {%- endif -%}
+                    {{- '}<tool_call|>' -}}
+                {%- endfor -%}
+                {%- set ns.prev_message_type = 'tool_call' -%}
+            {%- endif -%}
+
+            {%- set ns_tr_out = namespace(flag=false) -%}
+            {%- if message.get('tool_responses') -%}
+                {#- Legacy: tool_responses embedded on the assistant message (Google/Gemma native) -#}
+                {%- for tool_response in message['tool_responses'] -%}
+                    {{- format_tool_response_block(tool_response['name'] | default('unknown'), tool_response['response']) -}}
+                    {%- set ns_tr_out.flag = true -%}
+                    {%- set ns.prev_message_type = 'tool_response' -%}
+                {%- endfor -%}
+            {%- elif message.get('tool_calls') -%}
+                {#- OpenAI Chat Completions: forward-scan consecutive role:tool messages -#}
+                {%- set ns_tool_scan = namespace(stopped=false) -%}
+                {%- for k in range(loop.index0 + 1, loop_messages | length) -%}
+                    {%- if ns_tool_scan.stopped -%}
+                    {%- elif loop_messages[k]['role'] != 'tool' -%}
+                        {%- set ns_tool_scan.stopped = true -%}
+                    {%- else -%}
+                        {%- set follow = loop_messages[k] -%}
+                        {#- Resolve tool_call_id to function name -#}
+                        {%- set ns_tname = namespace(name=follow.get('name') | default('unknown')) -%}
+                        {%- for tc in message['tool_calls'] -%}
+                            {%- if tc.get('id') == follow.get('tool_call_id') -%}
+                                {%- set ns_tname.name = tc['function']['name'] -%}
+                            {%- endif -%}
+                        {%- endfor -%}
+                        {#- Handle content as string or content-parts array -#}
+                        {%- set tool_body = follow.get('content') -%}
+                        {%- if tool_body is string -%}
+                            {{- format_tool_response_block(ns_tname.name, tool_body) -}}
+                        {%- elif tool_body is sequence and tool_body is not string -%}
+                            {%- set ns_txt = namespace(s='') -%}
+                            {%- for part in tool_body -%}
+                                {%- if part.get('type') == 'text' -%}
+                                    {%- set ns_txt.s = ns_txt.s + (part.get('text') | default('')) -%}
+                                {%- endif -%}
+                            {%- endfor -%}
+                            {{- format_tool_response_block(ns_tname.name, ns_txt.s) -}}
+                        {%- else -%}
+                            {{- format_tool_response_block(ns_tname.name, tool_body) -}}
+                        {%- endif -%}
+                        {%- set ns_tr_out.flag = true -%}
+                        {%- set ns.prev_message_type = 'tool_response' -%}
+                    {%- endif -%}
+                {%- endfor -%}
+            {%- endif -%}
+
+            {%- set captured_content -%}
+            {%- if message['content'] is string -%}
+                {%- if role == 'model' -%}
+                    {{- strip_thinking(message['content']) -}}
+                {%- else -%}
+                    {{- message['content'] | trim -}}
+                {%- endif -%}
+            {%- elif message['content'] is sequence -%}
+                {%- for item in message['content'] -%}
+                    {%- if item['type'] == 'text' -%}
+                        {%- if role == 'model' -%}
+                            {{- strip_thinking(item['text']) -}}
+                        {%- else -%}
+                            {{- item['text'] | trim -}}
+                        {%- endif -%}
+                    {%- elif item['type'] == 'image' -%}
+                        {{- '<|image|>' -}}
+                        {%- set ns.prev_message_type = 'image' -%}
+                    {%- elif item['type'] == 'audio' -%}
+                        {{- '<|audio|>' -}}
+                        {%- set ns.prev_message_type = 'audio' -%}
+                    {%- elif item['type'] == 'video' -%}
+                        {{- '<|video|>' -}}
+                        {%- set ns.prev_message_type = 'video' -%}
+                    {%- endif -%}
+                {%- endfor -%}
+            {%- endif -%}
+            {%- endset -%}
+
+            {{- captured_content -}}
+            {%- set has_content = captured_content | trim | length > 0 -%}
+
+        {%- if ns.prev_message_type == 'tool_call' and not ns_tr_out.flag -%}
+            {{- '<|tool_response>' -}}
+        {%- elif not (ns_tr_out.flag and not has_content) -%}
+            {{- '<turn|>\n' -}}
+        {%- endif -%}
+    {%- endif -%}
+{%- endfor -%}
+
+{%- if add_generation_prompt -%}
+    {%- if ns.prev_message_type != 'tool_response' and ns.prev_message_type != 'tool_call' -%}
+        {{- '<|turn>model\n' -}}
+    {%- endif -%}
+{%- endif -%}

checkpoint-120/optimizer.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:095e1fcdf14af0658b82cfeea97af6ef9916881ed1b2df6af4546d0f79623b85
+size 52047117

checkpoint-120/processor_config.json

@@ -0,0 +1,75 @@
+{
+  "audio_ms_per_token": 40,
+  "audio_seq_length": 750,
+  "feature_extractor": {
+    "dither": 0.0,
+    "feature_extractor_type": "Gemma4AudioFeatureExtractor",
+    "feature_size": 128,
+    "fft_length": 512,
+    "fft_overdrive": false,
+    "frame_length": 320,
+    "hop_length": 160,
+    "input_scale_factor": 1.0,
+    "max_frequency": 8000.0,
+    "mel_floor": 0.001,
+    "min_frequency": 0.0,
+    "padding_side": "left",
+    "padding_value": 0.0,
+    "per_bin_mean": null,
+    "per_bin_stddev": null,
+    "preemphasis": 0.0,
+    "preemphasis_htk_flavor": true,
+    "return_attention_mask": true,
+    "sampling_rate": 16000
+  },
+  "image_processor": {
+    "do_convert_rgb": true,
+    "do_normalize": false,
+    "do_rescale": true,
+    "do_resize": true,
+    "image_mean": [
+      0.0,
+      0.0,
+      0.0
+    ],
+    "image_processor_type": "Gemma4ImageProcessor",
+    "image_seq_length": 280,
+    "image_std": [
+      1.0,
+      1.0,
+      1.0
+    ],
+    "max_soft_tokens": 280,
+    "patch_size": 16,
+    "pooling_kernel_size": 3,
+    "resample": 3,
+    "rescale_factor": 0.00392156862745098
+  },
+  "image_seq_length": 280,
+  "processor_class": "Gemma4Processor",
+  "video_processor": {
+    "do_convert_rgb": true,
+    "do_normalize": true,
+    "do_rescale": true,
+    "do_resize": true,
+    "do_sample_frames": true,
+    "image_mean": [
+      0.0,
+      0.0,
+      0.0
+    ],
+    "image_std": [
+      1.0,
+      1.0,
+      1.0
+    ],
+    "max_soft_tokens": 70,
+    "num_frames": 32,
+    "patch_size": 16,
+    "pooling_kernel_size": 3,
+    "resample": 3,
+    "rescale_factor": 0.00392156862745098,
+    "return_metadata": false,
+    "video_processor_type": "Gemma4VideoProcessor"
+  }
+}

checkpoint-120/rng_state.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:f1d565802a8e26c4e8a31328752b7a7fdc186d9401aa008e65697d0ad8c22e33
+size 14645

checkpoint-120/scaler.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:aa76f9fdc8f6bd88ee74f70ad294ae36bf2fe178b9965d6d01f072e8fa9198a8
+size 1383

checkpoint-120/scheduler.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:2d142e1b585c4fbc6a90a9d8170d8738b8abf95d0d40cf8046076286563427f1
+size 1465

checkpoint-120/tokenizer.json

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:cc8d3a0ce36466ccc1278bf987df5f71db1719b9ca6b4118264f45cb627bfe0f
+size 32169626

checkpoint-120/tokenizer_config.json

@@ -0,0 +1,289 @@
+{
+  "audio_token": "<|audio|>",
+  "backend": "tokenizers",
+  "boa_token": "<|audio>",
+  "boi_token": "<|image>",
+  "bos_token": "<bos>",
+  "eoa_token": "<audio|>",
+  "eoc_token": "<channel|>",
+  "eoi_token": "<image|>",
+  "eos_token": "<eos>",
+  "eot_token": "<turn|>",
+  "escape_token": "<|\"|>",
+  "etc_token": "<tool_call|>",
+  "etd_token": "<tool|>",
+  "etr_token": "<tool_response|>",
+  "extra_special_tokens": [
+    "<|video|>"
+  ],
+  "image_token": "<|image|>",
+  "is_local": false,
+  "mask_token": "<mask>",
+  "model_max_length": 131072,
+  "model_specific_special_tokens": {
+    "audio_token": "<|audio|>",
+    "boa_token": "<|audio>",
+    "boi_token": "<|image>",
+    "eoa_token": "<audio|>",
+    "eoc_token": "<channel|>",
+    "eoi_token": "<image|>",
+    "eot_token": "<turn|>",
+    "escape_token": "<|\"|>",
+    "etc_token": "<tool_call|>",
+    "etd_token": "<tool|>",
+    "etr_token": "<tool_response|>",
+    "image_token": "<|image|>",
+    "soc_token": "<|channel>",
+    "sot_token": "<|turn>",
+    "stc_token": "<|tool_call>",
+    "std_token": "<|tool>",
+    "str_token": "<|tool_response>",
+    "think_token": "<|think|>"
+  },
+  "pad_token": "<pad>",
+  "padding_side": "right",
+  "processor_class": "Gemma4Processor",
+  "response_schema": {
+    "properties": {
+      "content": {
+        "type": "string"
+      },
+      "role": {
+        "const": "assistant"
+      },
+      "thinking": {
+        "type": "string"
+      },
+      "tool_calls": {
+        "items": {
+          "properties": {
+            "function": {
+              "properties": {
+                "arguments": {
+                  "additionalProperties": {},
+                  "type": "object",
+                  "x-parser": "gemma4-tool-call"
+                },
+                "name": {
+                  "type": "string"
+                }
+              },
+              "type": "object",
+              "x-regex": "call\\:(?P<name>\\w+)(?P<arguments>\\{.*\\})"
+            },
+            "type": {
+              "const": "function"
+            }
+          },
+          "type": "object"
+        },
+        "type": "array",
+        "x-regex-iterator": "<\\|tool_call>(.*?)<tool_call\\|>"
+      }
+    },
+    "type": "object",
+    "x-regex": "(\\<\\|channel\\>thought\\n(?P<thinking>.*?)\\<channel\\|\\>)?(?P<tool_calls>\\<\\|tool_call\\>.*\\<tool_call\\|\\>)?(?P<content>(?:(?!\\<turn\\|\\>)(?!\\<\\|tool_response\\>).)+)?(?:\\<turn\\|\\>|\\<\\|tool_response\\>)?"
+  },
+  "soc_token": "<|channel>",
+  "sot_token": "<|turn>",
+  "stc_token": "<|tool_call>",
+  "std_token": "<|tool>",
+  "str_token": "<|tool_response>",
+  "think_token": "<|think|>",
+  "tokenizer_class": "GemmaTokenizer",
+  "unk_token": "<unk>",
+  "added_tokens_decoder": {
+    "0": {
+      "content": "<pad>",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    },
+    "1": {
+      "content": "<eos>",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    },
+    "2": {
+      "content": "<bos>",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    },
+    "3": {
+      "content": "<unk>",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    },
+    "4": {
+      "content": "<mask>",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    },
+    "46": {
+      "content": "<|tool>",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    },
+    "47": {
+      "content": "<tool|>",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    },
+    "48": {
+      "content": "<|tool_call>",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    },
+    "49": {
+      "content": "<tool_call|>",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    },
+    "50": {
+      "content": "<|tool_response>",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    },
+    "51": {
+      "content": "<tool_response|>",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    },
+    "52": {
+      "content": "<|\"|>",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    },
+    "98": {
+      "content": "<|think|>",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    },
+    "100": {
+      "content": "<|channel>",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    },
+    "101": {
+      "content": "<channel|>",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    },
+    "105": {
+      "content": "<|turn>",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    },
+    "106": {
+      "content": "<turn|>",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    },
+    "255999": {
+      "content": "<|image>",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    },
+    "256000": {
+      "content": "<|audio>",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    },
+    "258880": {
+      "content": "<|image|>",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    },
+    "258881": {
+      "content": "<|audio|>",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    },
+    "258882": {
+      "content": "<image|>",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    },
+    "258883": {
+      "content": "<audio|>",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    },
+    "258884": {
+      "content": "<|video|>",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    }
+  }
+}

checkpoint-120/trainer_state.json

@@ -0,0 +1,1234 @@
+{
+  "best_global_step": null,
+  "best_metric": null,
+  "best_model_checkpoint": null,
+  "epoch": 0.028402366863905324,
+  "eval_steps": 500,
+  "global_step": 120,
+  "is_hyper_param_search": false,
+  "is_local_process_zero": true,
+  "is_world_process_zero": true,
+  "log_history": [
+    {
+      "epoch": 0.00023668639053254438,
+      "grad_norm": NaN,
+      "learning_rate": 0.0,
+      "loss": 4.347962379455566,
+      "num_input_tokens_seen": 842,
+      "step": 1,
+      "train_runtime": 63.0289,
+      "train_tokens_per_second": 13.359
+    },
+    {
+      "epoch": 0.00047337278106508875,
+      "grad_norm": NaN,
+      "learning_rate": 0.0,
+      "loss": 4.634688854217529,
+      "num_input_tokens_seen": 1820,
+      "step": 2,
+      "train_runtime": 67.7033,
+      "train_tokens_per_second": 26.882
+    },
+    {
+      "epoch": 0.0007100591715976331,
+      "grad_norm": 13.944212913513184,
+      "learning_rate": 0.0,
+      "loss": 4.42241096496582,
+      "num_input_tokens_seen": 2754,
+      "step": 3,
+      "train_runtime": 72.324,
+      "train_tokens_per_second": 38.079
+    },
+    {
+      "epoch": 0.0009467455621301775,
+      "grad_norm": 13.445413589477539,
+      "learning_rate": 4e-05,
+      "loss": 4.682804107666016,
+      "num_input_tokens_seen": 3700,
+      "step": 4,
+      "train_runtime": 75.3925,
+      "train_tokens_per_second": 49.077
+    },
+    {
+      "epoch": 0.001183431952662722,
+      "grad_norm": 10.576727867126465,
+      "learning_rate": 8e-05,
+      "loss": 4.166159629821777,
+      "num_input_tokens_seen": 4714,
+      "step": 5,
+      "train_runtime": 78.474,
+      "train_tokens_per_second": 60.071
+    },
+    {
+      "epoch": 0.0014201183431952662,
+      "grad_norm": 8.077850341796875,
+      "learning_rate": 0.00012,
+      "loss": 3.2006261348724365,
+      "num_input_tokens_seen": 5674,
+      "step": 6,
+      "train_runtime": 81.6139,
+      "train_tokens_per_second": 69.522
+    },
+    {
+      "epoch": 0.0016568047337278107,
+      "grad_norm": 6.60789680480957,
+      "learning_rate": 0.00016,
+      "loss": 2.7067415714263916,
+      "num_input_tokens_seen": 6646,
+      "step": 7,
+      "train_runtime": 84.786,
+      "train_tokens_per_second": 78.386
+    },
+    {
+      "epoch": 0.001893491124260355,
+      "grad_norm": 9.175209045410156,
+      "learning_rate": 0.0002,
+      "loss": 2.367570638656616,
+      "num_input_tokens_seen": 7518,
+      "step": 8,
+      "train_runtime": 87.8178,
+      "train_tokens_per_second": 85.609
+    },
+    {
+      "epoch": 0.0021301775147928993,
+      "grad_norm": 3.438948631286621,
+      "learning_rate": 0.00019891891891891895,
+      "loss": 2.1013119220733643,
+      "num_input_tokens_seen": 8470,
+      "step": 9,
+      "train_runtime": 90.9458,
+      "train_tokens_per_second": 93.132
+    },
+    {
+      "epoch": 0.002366863905325444,
+      "grad_norm": 3.459472894668579,
+      "learning_rate": 0.00019783783783783784,
+      "loss": 1.8991940021514893,
+      "num_input_tokens_seen": 9458,
+      "step": 10,
+      "train_runtime": 94.0577,
+      "train_tokens_per_second": 100.555
+    },
+    {
+      "epoch": 0.0026035502958579883,
+      "grad_norm": 2.169750928878784,
+      "learning_rate": 0.00019675675675675678,
+      "loss": 1.7395055294036865,
+      "num_input_tokens_seen": 10456,
+      "step": 11,
+      "train_runtime": 97.2068,
+      "train_tokens_per_second": 107.565
+    },
+    {
+      "epoch": 0.0028402366863905324,
+      "grad_norm": 1.8638927936553955,
+      "learning_rate": 0.00019567567567567567,
+      "loss": 1.5622950792312622,
+      "num_input_tokens_seen": 11410,
+      "step": 12,
+      "train_runtime": 100.2911,
+      "train_tokens_per_second": 113.769
+    },
+    {
+      "epoch": 0.003076923076923077,
+      "grad_norm": 1.4741116762161255,
+      "learning_rate": 0.00019459459459459462,
+      "loss": 1.392699956893921,
+      "num_input_tokens_seen": 12316,
+      "step": 13,
+      "train_runtime": 103.3664,
+      "train_tokens_per_second": 119.149
+    },
+    {
+      "epoch": 0.0033136094674556214,
+      "grad_norm": 1.3238699436187744,
+      "learning_rate": 0.00019351351351351353,
+      "loss": 1.2535074949264526,
+      "num_input_tokens_seen": 13256,
+      "step": 14,
+      "train_runtime": 106.4031,
+      "train_tokens_per_second": 124.583
+    },
+    {
+      "epoch": 0.0035502958579881655,
+      "grad_norm": 1.276484489440918,
+      "learning_rate": 0.00019243243243243245,
+      "loss": 1.135048508644104,
+      "num_input_tokens_seen": 14228,
+      "step": 15,
+      "train_runtime": 109.4909,
+      "train_tokens_per_second": 129.947
+    },
+    {
+      "epoch": 0.00378698224852071,
+      "grad_norm": 1.1560865640640259,
+      "learning_rate": 0.00019135135135135137,
+      "loss": 1.0317097902297974,
+      "num_input_tokens_seen": 15192,
+      "step": 16,
+      "train_runtime": 112.5741,
+      "train_tokens_per_second": 134.951
+    },
+    {
+      "epoch": 0.004023668639053254,
+      "grad_norm": 1.1331353187561035,
+      "learning_rate": 0.00019027027027027028,
+      "loss": 0.9967219233512878,
+      "num_input_tokens_seen": 16130,
+      "step": 17,
+      "train_runtime": 115.6495,
+      "train_tokens_per_second": 139.473
+    },
+    {
+      "epoch": 0.004260355029585799,
+      "grad_norm": 1.1567702293395996,
+      "learning_rate": 0.0001891891891891892,
+      "loss": 0.905368447303772,
+      "num_input_tokens_seen": 17078,
+      "step": 18,
+      "train_runtime": 118.6796,
+      "train_tokens_per_second": 143.9
+    },
+    {
+      "epoch": 0.004497041420118343,
+      "grad_norm": 0.9157600998878479,
+      "learning_rate": 0.00018810810810810814,
+      "loss": 0.8075690865516663,
+      "num_input_tokens_seen": 18062,
+      "step": 19,
+      "train_runtime": 121.8602,
+      "train_tokens_per_second": 148.219
+    },
+    {
+      "epoch": 0.004733727810650888,
+      "grad_norm": 0.8306605815887451,
+      "learning_rate": 0.00018702702702702703,
+      "loss": 0.8007175922393799,
+      "num_input_tokens_seen": 19078,
+      "step": 20,
+      "train_runtime": 125.0019,
+      "train_tokens_per_second": 152.622
+    },
+    {
+      "epoch": 0.004970414201183432,
+      "grad_norm": 0.690018355846405,
+      "learning_rate": 0.00018594594594594597,
+      "loss": 0.7810791730880737,
+      "num_input_tokens_seen": 20068,
+      "step": 21,
+      "train_runtime": 128.0932,
+      "train_tokens_per_second": 156.667
+    },
+    {
+      "epoch": 0.005207100591715977,
+      "grad_norm": 1.4768867492675781,
+      "learning_rate": 0.00018486486486486486,
+      "loss": 0.7172120809555054,
+      "num_input_tokens_seen": 20972,
+      "step": 22,
+      "train_runtime": 131.0901,
+      "train_tokens_per_second": 159.982
+    },
+    {
+      "epoch": 0.00544378698224852,
+      "grad_norm": 0.7999809980392456,
+      "learning_rate": 0.0001837837837837838,
+      "loss": 0.6333726048469543,
+      "num_input_tokens_seen": 21900,
+      "step": 23,
+      "train_runtime": 134.212,
+      "train_tokens_per_second": 163.175
+    },
+    {
+      "epoch": 0.005680473372781065,
+      "grad_norm": 0.9285996556282043,
+      "learning_rate": 0.00018270270270270272,
+      "loss": 0.6750729084014893,
+      "num_input_tokens_seen": 22770,
+      "step": 24,
+      "train_runtime": 137.3193,
+      "train_tokens_per_second": 165.818
+    },
+    {
+      "epoch": 0.005917159763313609,
+      "grad_norm": 0.7733820080757141,
+      "learning_rate": 0.00018162162162162164,
+      "loss": 0.672032356262207,
+      "num_input_tokens_seen": 23746,
+      "step": 25,
+      "train_runtime": 140.3175,
+      "train_tokens_per_second": 169.23
+    },
+    {
+      "epoch": 0.006153846153846154,
+      "grad_norm": 0.73944091796875,
+      "learning_rate": 0.00018054054054054055,
+      "loss": 0.6716101169586182,
+      "num_input_tokens_seen": 24716,
+      "step": 26,
+      "train_runtime": 143.3683,
+      "train_tokens_per_second": 172.395
+    },
+    {
+      "epoch": 0.006390532544378698,
+      "grad_norm": 0.7659372091293335,
+      "learning_rate": 0.00017945945945945947,
+      "loss": 0.6067175269126892,
+      "num_input_tokens_seen": 25724,
+      "step": 27,
+      "train_runtime": 146.5377,
+      "train_tokens_per_second": 175.545
+    },
+    {
+      "epoch": 0.006627218934911243,
+      "grad_norm": 0.5428617000579834,
+      "learning_rate": 0.00017837837837837839,
+      "loss": 0.6083395481109619,
+      "num_input_tokens_seen": 26712,
+      "step": 28,
+      "train_runtime": 149.6429,
+      "train_tokens_per_second": 178.505
+    },
+    {
+      "epoch": 0.006863905325443787,
+      "grad_norm": 0.5915114283561707,
+      "learning_rate": 0.00017729729729729733,
+      "loss": 0.6463742256164551,
+      "num_input_tokens_seen": 27704,
+      "step": 29,
+      "train_runtime": 152.7501,
+      "train_tokens_per_second": 181.368
+    },
+    {
+      "epoch": 0.007100591715976331,
+      "grad_norm": 1.3350757360458374,
+      "learning_rate": 0.00017621621621621622,
+      "loss": 0.5705698132514954,
+      "num_input_tokens_seen": 28648,
+      "step": 30,
+      "train_runtime": 155.8918,
+      "train_tokens_per_second": 183.768
+    },
+    {
+      "epoch": 0.0073372781065088755,
+      "grad_norm": 0.68421471118927,
+      "learning_rate": 0.00017513513513513516,
+      "loss": 0.5660746097564697,
+      "num_input_tokens_seen": 29622,
+      "step": 31,
+      "train_runtime": 163.3209,
+      "train_tokens_per_second": 181.373
+    },
+    {
+      "epoch": 0.00757396449704142,
+      "grad_norm": 0.5762604475021362,
+      "learning_rate": 0.00017405405405405405,
+      "loss": 0.5483309030532837,
+      "num_input_tokens_seen": 30534,
+      "step": 32,
+      "train_runtime": 166.5185,
+      "train_tokens_per_second": 183.367
+    },
+    {
+      "epoch": 0.0078106508875739646,
+      "grad_norm": 0.5751784443855286,
+      "learning_rate": 0.000172972972972973,
+      "loss": 0.5207005739212036,
+      "num_input_tokens_seen": 31458,
+      "step": 33,
+      "train_runtime": 169.7055,
+      "train_tokens_per_second": 185.368
+    },
+    {
+      "epoch": 0.008047337278106508,
+      "grad_norm": 0.5752039551734924,
+      "learning_rate": 0.0001718918918918919,
+      "loss": 0.5534584522247314,
+      "num_input_tokens_seen": 32424,
+      "step": 34,
+      "train_runtime": 172.9184,
+      "train_tokens_per_second": 187.51
+    },
+    {
+      "epoch": 0.008284023668639054,
+      "grad_norm": 0.5918363332748413,
+      "learning_rate": 0.00017081081081081083,
+      "loss": 0.482683002948761,
+      "num_input_tokens_seen": 33398,
+      "step": 35,
+      "train_runtime": 176.2158,
+      "train_tokens_per_second": 189.529
+    },
+    {
+      "epoch": 0.008520710059171597,
+      "grad_norm": 0.6921846270561218,
+      "learning_rate": 0.00016972972972972974,
+      "loss": 0.46112507581710815,
+      "num_input_tokens_seen": 34324,
+      "step": 36,
+      "train_runtime": 179.3173,
+      "train_tokens_per_second": 191.415
+    },
+    {
+      "epoch": 0.008757396449704143,
+      "grad_norm": 0.6429721117019653,
+      "learning_rate": 0.00016864864864864866,
+      "loss": 0.45629197359085083,
+      "num_input_tokens_seen": 35270,
+      "step": 37,
+      "train_runtime": 182.3558,
+      "train_tokens_per_second": 193.413
+    },
+    {
+      "epoch": 0.008994082840236686,
+      "grad_norm": 0.5477020740509033,
+      "learning_rate": 0.00016756756756756757,
+      "loss": 0.4547877907752991,
+      "num_input_tokens_seen": 36206,
+      "step": 38,
+      "train_runtime": 185.4483,
+      "train_tokens_per_second": 195.235
+    },
+    {
+      "epoch": 0.009230769230769232,
+      "grad_norm": 0.6158634424209595,
+      "learning_rate": 0.00016648648648648652,
+      "loss": 0.367482990026474,
+      "num_input_tokens_seen": 37080,
+      "step": 39,
+      "train_runtime": 188.5114,
+      "train_tokens_per_second": 196.699
+    },
+    {
+      "epoch": 0.009467455621301775,
+      "grad_norm": 0.5405091643333435,
+      "learning_rate": 0.0001654054054054054,
+      "loss": 0.42049410939216614,
+      "num_input_tokens_seen": 38030,
+      "step": 40,
+      "train_runtime": 191.5986,
+      "train_tokens_per_second": 198.488
+    },
+    {
+      "epoch": 0.009704142011834319,
+      "grad_norm": 0.6389183402061462,
+      "learning_rate": 0.00016432432432432435,
+      "loss": 0.3935014307498932,
+      "num_input_tokens_seen": 38942,
+      "step": 41,
+      "train_runtime": 194.8426,
+      "train_tokens_per_second": 199.864
+    },
+    {
+      "epoch": 0.009940828402366864,
+      "grad_norm": 0.6742956042289734,
+      "learning_rate": 0.00016324324324324324,
+      "loss": 0.4373692274093628,
+      "num_input_tokens_seen": 39902,
+      "step": 42,
+      "train_runtime": 197.8938,
+      "train_tokens_per_second": 201.633
+    },
+    {
+      "epoch": 0.010177514792899408,
+      "grad_norm": 0.6083794236183167,
+      "learning_rate": 0.00016216216216216218,
+      "loss": 0.3776765465736389,
+      "num_input_tokens_seen": 40858,
+      "step": 43,
+      "train_runtime": 200.9708,
+      "train_tokens_per_second": 203.303
+    },
+    {
+      "epoch": 0.010414201183431953,
+      "grad_norm": 0.5469992160797119,
+      "learning_rate": 0.0001610810810810811,
+      "loss": 0.31133151054382324,
+      "num_input_tokens_seen": 41760,
+      "step": 44,
+      "train_runtime": 204.1304,
+      "train_tokens_per_second": 204.575
+    },
+    {
+      "epoch": 0.010650887573964497,
+      "grad_norm": 0.6452498435974121,
+      "learning_rate": 0.00016,
+      "loss": 0.42721521854400635,
+      "num_input_tokens_seen": 42740,
+      "step": 45,
+      "train_runtime": 207.1845,
+      "train_tokens_per_second": 206.29
+    },
+    {
+      "epoch": 0.01088757396449704,
+      "grad_norm": 0.5988945960998535,
+      "learning_rate": 0.00015891891891891893,
+      "loss": 0.41375258564949036,
+      "num_input_tokens_seen": 43750,
+      "step": 46,
+      "train_runtime": 210.2912,
+      "train_tokens_per_second": 208.045
+    },
+    {
+      "epoch": 0.011124260355029586,
+      "grad_norm": 0.6452038288116455,
+      "learning_rate": 0.00015783783783783785,
+      "loss": 0.3485276699066162,
+      "num_input_tokens_seen": 44690,
+      "step": 47,
+      "train_runtime": 213.3684,
+      "train_tokens_per_second": 209.45
+    },
+    {
+      "epoch": 0.01136094674556213,
+      "grad_norm": 0.7041454911231995,
+      "learning_rate": 0.00015675675675675676,
+      "loss": 0.3296637535095215,
+      "num_input_tokens_seen": 45666,
+      "step": 48,
+      "train_runtime": 216.4459,
+      "train_tokens_per_second": 210.981
+    },
+    {
+      "epoch": 0.011597633136094675,
+      "grad_norm": 0.6726324558258057,
+      "learning_rate": 0.0001556756756756757,
+      "loss": 0.3179457187652588,
+      "num_input_tokens_seen": 46560,
+      "step": 49,
+      "train_runtime": 219.4697,
+      "train_tokens_per_second": 212.148
+    },
+    {
+      "epoch": 0.011834319526627219,
+      "grad_norm": 0.7513703107833862,
+      "learning_rate": 0.0001545945945945946,
+      "loss": 0.3722391426563263,
+      "num_input_tokens_seen": 47528,
+      "step": 50,
+      "train_runtime": 222.596,
+      "train_tokens_per_second": 213.517
+    },
+    {
+      "epoch": 0.012071005917159764,
+      "grad_norm": 0.6454160213470459,
+      "learning_rate": 0.00015351351351351354,
+      "loss": 0.283376544713974,
+      "num_input_tokens_seen": 48468,
+      "step": 51,
+      "train_runtime": 225.7262,
+      "train_tokens_per_second": 214.72
+    },
+    {
+      "epoch": 0.012307692307692308,
+      "grad_norm": 0.9116244316101074,
+      "learning_rate": 0.00015243243243243243,
+      "loss": 0.4286752939224243,
+      "num_input_tokens_seen": 49444,
+      "step": 52,
+      "train_runtime": 228.803,
+      "train_tokens_per_second": 216.099
+    },
+    {
+      "epoch": 0.012544378698224851,
+      "grad_norm": 0.6157099604606628,
+      "learning_rate": 0.00015135135135135137,
+      "loss": 0.27355721592903137,
+      "num_input_tokens_seen": 50424,
+      "step": 53,
+      "train_runtime": 231.8413,
+      "train_tokens_per_second": 217.494
+    },
+    {
+      "epoch": 0.012781065088757397,
+      "grad_norm": 0.6335808038711548,
+      "learning_rate": 0.00015027027027027028,
+      "loss": 0.37197017669677734,
+      "num_input_tokens_seen": 51328,
+      "step": 54,
+      "train_runtime": 234.9265,
+      "train_tokens_per_second": 218.485
+    },
+    {
+      "epoch": 0.01301775147928994,
+      "grad_norm": 0.6838424205780029,
+      "learning_rate": 0.0001491891891891892,
+      "loss": 0.3504602909088135,
+      "num_input_tokens_seen": 52274,
+      "step": 55,
+      "train_runtime": 238.0114,
+      "train_tokens_per_second": 219.628
+    },
+    {
+      "epoch": 0.013254437869822486,
+      "grad_norm": 0.6566418409347534,
+      "learning_rate": 0.00014810810810810812,
+      "loss": 0.3189927935600281,
+      "num_input_tokens_seen": 53214,
+      "step": 56,
+      "train_runtime": 241.0892,
+      "train_tokens_per_second": 220.723
+    },
+    {
+      "epoch": 0.01349112426035503,
+      "grad_norm": 0.6112971901893616,
+      "learning_rate": 0.00014702702702702703,
+      "loss": 0.3080369830131531,
+      "num_input_tokens_seen": 54162,
+      "step": 57,
+      "train_runtime": 244.2461,
+      "train_tokens_per_second": 221.752
+    },
+    {
+      "epoch": 0.013727810650887575,
+      "grad_norm": 0.6469757556915283,
+      "learning_rate": 0.00014594594594594595,
+      "loss": 0.24279898405075073,
+      "num_input_tokens_seen": 55158,
+      "step": 58,
+      "train_runtime": 247.4064,
+      "train_tokens_per_second": 222.945
+    },
+    {
+      "epoch": 0.013964497041420118,
+      "grad_norm": 0.7099384665489197,
+      "learning_rate": 0.0001448648648648649,
+      "loss": 0.31188705563545227,
+      "num_input_tokens_seen": 56096,
+      "step": 59,
+      "train_runtime": 250.4708,
+      "train_tokens_per_second": 223.962
+    },
+    {
+      "epoch": 0.014201183431952662,
+      "grad_norm": 0.5927040576934814,
+      "learning_rate": 0.00014378378378378378,
+      "loss": 0.25696688890457153,
+      "num_input_tokens_seen": 57012,
+      "step": 60,
+      "train_runtime": 253.7131,
+      "train_tokens_per_second": 224.711
+    },
+    {
+      "epoch": 0.014437869822485207,
+      "grad_norm": 0.5483338236808777,
+      "learning_rate": 0.00014270270270270272,
+      "loss": 0.2725352644920349,
+      "num_input_tokens_seen": 58036,
+      "step": 61,
+      "train_runtime": 260.2844,
+      "train_tokens_per_second": 222.971
+    },
+    {
+      "epoch": 0.014674556213017751,
+      "grad_norm": 0.6806847453117371,
+      "learning_rate": 0.00014162162162162161,
+      "loss": 0.31959983706474304,
+      "num_input_tokens_seen": 59026,
+      "step": 62,
+      "train_runtime": 263.3802,
+      "train_tokens_per_second": 224.109
+    },
+    {
+      "epoch": 0.014911242603550296,
+      "grad_norm": 0.6916660070419312,
+      "learning_rate": 0.00014054054054054056,
+      "loss": 0.312305748462677,
+      "num_input_tokens_seen": 59982,
+      "step": 63,
+      "train_runtime": 266.3794,
+      "train_tokens_per_second": 225.175
+    },
+    {
+      "epoch": 0.01514792899408284,
+      "grad_norm": 0.5516266226768494,
+      "learning_rate": 0.00013945945945945947,
+      "loss": 0.2653953433036804,
+      "num_input_tokens_seen": 60926,
+      "step": 64,
+      "train_runtime": 269.3893,
+      "train_tokens_per_second": 226.163
+    },
+    {
+      "epoch": 0.015384615384615385,
+      "grad_norm": 0.5579270720481873,
+      "learning_rate": 0.0001383783783783784,
+      "loss": 0.20462818443775177,
+      "num_input_tokens_seen": 61844,
+      "step": 65,
+      "train_runtime": 272.3982,
+      "train_tokens_per_second": 227.035
+    },
+    {
+      "epoch": 0.015621301775147929,
+      "grad_norm": 0.7645660638809204,
+      "learning_rate": 0.0001372972972972973,
+      "loss": 0.2650893032550812,
+      "num_input_tokens_seen": 62766,
+      "step": 66,
+      "train_runtime": 275.404,
+      "train_tokens_per_second": 227.905
+    },
+    {
+      "epoch": 0.015857988165680473,
+      "grad_norm": 0.5974738001823425,
+      "learning_rate": 0.00013621621621621622,
+      "loss": 0.21247778832912445,
+      "num_input_tokens_seen": 63690,
+      "step": 67,
+      "train_runtime": 278.4021,
+      "train_tokens_per_second": 228.77
+    },
+    {
+      "epoch": 0.016094674556213016,
+      "grad_norm": 0.5831193327903748,
+      "learning_rate": 0.00013513513513513514,
+      "loss": 0.2024172842502594,
+      "num_input_tokens_seen": 64496,
+      "step": 68,
+      "train_runtime": 281.4313,
+      "train_tokens_per_second": 229.171
+    },
+    {
+      "epoch": 0.016331360946745564,
+      "grad_norm": 0.8678795695304871,
+      "learning_rate": 0.00013405405405405408,
+      "loss": 0.31490638852119446,
+      "num_input_tokens_seen": 65460,
+      "step": 69,
+      "train_runtime": 284.6137,
+      "train_tokens_per_second": 229.996
+    },
+    {
+      "epoch": 0.016568047337278107,
+      "grad_norm": 0.7611344456672668,
+      "learning_rate": 0.00013297297297297297,
+      "loss": 0.24661925435066223,
+      "num_input_tokens_seen": 66374,
+      "step": 70,
+      "train_runtime": 287.7742,
+      "train_tokens_per_second": 230.646
+    },
+    {
+      "epoch": 0.01680473372781065,
+      "grad_norm": 0.6685308814048767,
+      "learning_rate": 0.0001318918918918919,
+      "loss": 0.1843535602092743,
+      "num_input_tokens_seen": 67112,
+      "step": 71,
+      "train_runtime": 290.9321,
+      "train_tokens_per_second": 230.679
+    },
+    {
+      "epoch": 0.017041420118343194,
+      "grad_norm": 0.6150883436203003,
+      "learning_rate": 0.0001308108108108108,
+      "loss": 0.23372295498847961,
+      "num_input_tokens_seen": 68154,
+      "step": 72,
+      "train_runtime": 294.0809,
+      "train_tokens_per_second": 231.753
+    },
+    {
+      "epoch": 0.017278106508875738,
+      "grad_norm": 0.6938812732696533,
+      "learning_rate": 0.00012972972972972974,
+      "loss": 0.22619186341762543,
+      "num_input_tokens_seen": 69102,
+      "step": 73,
+      "train_runtime": 297.1843,
+      "train_tokens_per_second": 232.522
+    },
+    {
+      "epoch": 0.017514792899408285,
+      "grad_norm": 0.617787778377533,
+      "learning_rate": 0.00012864864864864866,
+      "loss": 0.2535328269004822,
+      "num_input_tokens_seen": 70010,
+      "step": 74,
+      "train_runtime": 300.2851,
+      "train_tokens_per_second": 233.145
+    },
+    {
+      "epoch": 0.01775147928994083,
+      "grad_norm": 0.6884900331497192,
+      "learning_rate": 0.00012756756756756758,
+      "loss": 0.21632739901542664,
+      "num_input_tokens_seen": 70940,
+      "step": 75,
+      "train_runtime": 303.3533,
+      "train_tokens_per_second": 233.853
+    },
+    {
+      "epoch": 0.017988165680473372,
+      "grad_norm": 0.5782189965248108,
+      "learning_rate": 0.0001264864864864865,
+      "loss": 0.20167675614356995,
+      "num_input_tokens_seen": 71862,
+      "step": 76,
+      "train_runtime": 306.4503,
+      "train_tokens_per_second": 234.498
+    },
+    {
+      "epoch": 0.018224852071005916,
+      "grad_norm": 0.6541483402252197,
+      "learning_rate": 0.0001254054054054054,
+      "loss": 0.23231221735477448,
+      "num_input_tokens_seen": 72812,
+      "step": 77,
+      "train_runtime": 309.5743,
+      "train_tokens_per_second": 235.2
+    },
+    {
+      "epoch": 0.018461538461538463,
+      "grad_norm": 0.7524886727333069,
+      "learning_rate": 0.00012432432432432433,
+      "loss": 0.27632662653923035,
+      "num_input_tokens_seen": 73774,
+      "step": 78,
+      "train_runtime": 312.6963,
+      "train_tokens_per_second": 235.929
+    },
+    {
+      "epoch": 0.018698224852071007,
+      "grad_norm": 0.716282308101654,
+      "learning_rate": 0.00012324324324324327,
+      "loss": 0.2734939754009247,
+      "num_input_tokens_seen": 74716,
+      "step": 79,
+      "train_runtime": 315.7612,
+      "train_tokens_per_second": 236.622
+    },
+    {
+      "epoch": 0.01893491124260355,
+      "grad_norm": 0.7010631561279297,
+      "learning_rate": 0.00012216216216216216,
+      "loss": 0.2774362564086914,
+      "num_input_tokens_seen": 75692,
+      "step": 80,
+      "train_runtime": 318.7983,
+      "train_tokens_per_second": 237.429
+    },
+    {
+      "epoch": 0.019171597633136094,
+      "grad_norm": 0.6561240553855896,
+      "learning_rate": 0.00012108108108108109,
+      "loss": 0.21640686690807343,
+      "num_input_tokens_seen": 76558,
+      "step": 81,
+      "train_runtime": 321.889,
+      "train_tokens_per_second": 237.84
+    },
+    {
+      "epoch": 0.019408284023668638,
+      "grad_norm": 0.5552831888198853,
+      "learning_rate": 0.00012,
+      "loss": 0.21232956647872925,
+      "num_input_tokens_seen": 77408,
+      "step": 82,
+      "train_runtime": 325.0469,
+      "train_tokens_per_second": 238.144
+    },
+    {
+      "epoch": 0.019644970414201185,
+      "grad_norm": 0.5905120372772217,
+      "learning_rate": 0.00011891891891891893,
+      "loss": 0.22443550825119019,
+      "num_input_tokens_seen": 78278,
+      "step": 83,
+      "train_runtime": 328.099,
+      "train_tokens_per_second": 238.58
+    },
+    {
+      "epoch": 0.01988165680473373,
+      "grad_norm": 0.6606366634368896,
+      "learning_rate": 0.00011783783783783784,
+      "loss": 0.2400747388601303,
+      "num_input_tokens_seen": 79262,
+      "step": 84,
+      "train_runtime": 331.1361,
+      "train_tokens_per_second": 239.364
+    },
+    {
+      "epoch": 0.020118343195266272,
+      "grad_norm": 0.6508055329322815,
+      "learning_rate": 0.00011675675675675676,
+      "loss": 0.19072499871253967,
+      "num_input_tokens_seen": 80144,
+      "step": 85,
+      "train_runtime": 334.2158,
+      "train_tokens_per_second": 239.797
+    },
+    {
+      "epoch": 0.020355029585798816,
+      "grad_norm": 0.606562614440918,
+      "learning_rate": 0.00011567567567567568,
+      "loss": 0.20951862633228302,
+      "num_input_tokens_seen": 81108,
+      "step": 86,
+      "train_runtime": 337.3105,
+      "train_tokens_per_second": 240.455
+    },
+    {
+      "epoch": 0.02059171597633136,
+      "grad_norm": 0.6757521629333496,
+      "learning_rate": 0.00011459459459459461,
+      "loss": 0.17614495754241943,
+      "num_input_tokens_seen": 82032,
+      "step": 87,
+      "train_runtime": 340.3438,
+      "train_tokens_per_second": 241.027
+    },
+    {
+      "epoch": 0.020828402366863907,
+      "grad_norm": 0.671481728553772,
+      "learning_rate": 0.00011351351351351351,
+      "loss": 0.1901710331439972,
+      "num_input_tokens_seen": 82954,
+      "step": 88,
+      "train_runtime": 343.4059,
+      "train_tokens_per_second": 241.563
+    },
+    {
+      "epoch": 0.02106508875739645,
+      "grad_norm": 0.5919027924537659,
+      "learning_rate": 0.00011243243243243244,
+      "loss": 0.1563737988471985,
+      "num_input_tokens_seen": 83880,
+      "step": 89,
+      "train_runtime": 346.5125,
+      "train_tokens_per_second": 242.069
+    },
+    {
+      "epoch": 0.021301775147928994,
+      "grad_norm": 0.7108309268951416,
+      "learning_rate": 0.00011135135135135135,
+      "loss": 0.17256894707679749,
+      "num_input_tokens_seen": 84852,
+      "step": 90,
+      "train_runtime": 349.6508,
+      "train_tokens_per_second": 242.676
+    },
+    {
+      "epoch": 0.021538461538461538,
+      "grad_norm": 0.8608420491218567,
+      "learning_rate": 0.00011027027027027029,
+      "loss": 0.1845530867576599,
+      "num_input_tokens_seen": 85820,
+      "step": 91,
+      "train_runtime": 356.267,
+      "train_tokens_per_second": 240.887
+    },
+    {
+      "epoch": 0.02177514792899408,
+      "grad_norm": 0.9677010774612427,
+      "learning_rate": 0.00010918918918918919,
+      "loss": 0.24358105659484863,
+      "num_input_tokens_seen": 86770,
+      "step": 92,
+      "train_runtime": 359.3722,
+      "train_tokens_per_second": 241.449
+    },
+    {
+      "epoch": 0.02201183431952663,
+      "grad_norm": 0.6302966475486755,
+      "learning_rate": 0.00010810810810810812,
+      "loss": 0.18155133724212646,
+      "num_input_tokens_seen": 87736,
+      "step": 93,
+      "train_runtime": 362.5874,
+      "train_tokens_per_second": 241.972
+    },
+    {
+      "epoch": 0.022248520710059172,
+      "grad_norm": 0.7171812653541565,
+      "learning_rate": 0.00010702702702702702,
+      "loss": 0.15349116921424866,
+      "num_input_tokens_seen": 88626,
+      "step": 94,
+      "train_runtime": 365.7055,
+      "train_tokens_per_second": 242.343
+    },
+    {
+      "epoch": 0.022485207100591716,
+      "grad_norm": 0.7326887845993042,
+      "learning_rate": 0.00010594594594594595,
+      "loss": 0.18243758380413055,
+      "num_input_tokens_seen": 89548,
+      "step": 95,
+      "train_runtime": 368.799,
+      "train_tokens_per_second": 242.81
+    },
+    {
+      "epoch": 0.02272189349112426,
+      "grad_norm": 0.6686019897460938,
+      "learning_rate": 0.00010486486486486487,
+      "loss": 0.15622465312480927,
+      "num_input_tokens_seen": 90504,
+      "step": 96,
+      "train_runtime": 371.8404,
+      "train_tokens_per_second": 243.395
+    },
+    {
+      "epoch": 0.022958579881656806,
+      "grad_norm": 0.6306503415107727,
+      "learning_rate": 0.0001037837837837838,
+      "loss": 0.1272117793560028,
+      "num_input_tokens_seen": 91454,
+      "step": 97,
+      "train_runtime": 375.0199,
+      "train_tokens_per_second": 243.864
+    },
+    {
+      "epoch": 0.02319526627218935,
+      "grad_norm": 0.6068493127822876,
+      "learning_rate": 0.0001027027027027027,
+      "loss": 0.1577155441045761,
+      "num_input_tokens_seen": 92466,
+      "step": 98,
+      "train_runtime": 378.0978,
+      "train_tokens_per_second": 244.556
+    },
+    {
+      "epoch": 0.023431952662721894,
+      "grad_norm": 0.7263635993003845,
+      "learning_rate": 0.00010162162162162163,
+      "loss": 0.1845340132713318,
+      "num_input_tokens_seen": 93398,
+      "step": 99,
+      "train_runtime": 381.1358,
+      "train_tokens_per_second": 245.052
+    },
+    {
+      "epoch": 0.023668639053254437,
+      "grad_norm": 0.6466794013977051,
+      "learning_rate": 0.00010054054054054053,
+      "loss": 0.14443959295749664,
+      "num_input_tokens_seen": 94230,
+      "step": 100,
+      "train_runtime": 384.2906,
+      "train_tokens_per_second": 245.205
+    },
+    {
+      "epoch": 0.02390532544378698,
+      "grad_norm": 0.6924043297767639,
+      "learning_rate": 9.945945945945948e-05,
+      "loss": 0.18473166227340698,
+      "num_input_tokens_seen": 95132,
+      "step": 101,
+      "train_runtime": 387.5005,
+      "train_tokens_per_second": 245.502
+    },
+    {
+      "epoch": 0.024142011834319528,
+      "grad_norm": 0.732337236404419,
+      "learning_rate": 9.837837837837839e-05,
+      "loss": 0.16353662312030792,
+      "num_input_tokens_seen": 96080,
+      "step": 102,
+      "train_runtime": 390.584,
+      "train_tokens_per_second": 245.991
+    },
+    {
+      "epoch": 0.02437869822485207,
+      "grad_norm": 0.5956932902336121,
+      "learning_rate": 9.729729729729731e-05,
+      "loss": 0.16359847784042358,
+      "num_input_tokens_seen": 97048,
+      "step": 103,
+      "train_runtime": 393.6474,
+      "train_tokens_per_second": 246.535
+    },
+    {
+      "epoch": 0.024615384615384615,
+      "grad_norm": 0.6137388348579407,
+      "learning_rate": 9.621621621621622e-05,
+      "loss": 0.15779417753219604,
+      "num_input_tokens_seen": 97986,
+      "step": 104,
+      "train_runtime": 396.7042,
+      "train_tokens_per_second": 247.0
+    },
+    {
+      "epoch": 0.02485207100591716,
+      "grad_norm": 0.7936599254608154,
+      "learning_rate": 9.513513513513514e-05,
+      "loss": 0.21357379853725433,
+      "num_input_tokens_seen": 98894,
+      "step": 105,
+      "train_runtime": 399.8228,
+      "train_tokens_per_second": 247.345
+    },
+    {
+      "epoch": 0.025088757396449703,
+      "grad_norm": 0.6574507355690002,
+      "learning_rate": 9.405405405405407e-05,
+      "loss": 0.1685573309659958,
+      "num_input_tokens_seen": 99856,
+      "step": 106,
+      "train_runtime": 402.8867,
+      "train_tokens_per_second": 247.851
+    },
+    {
+      "epoch": 0.02532544378698225,
+      "grad_norm": 0.5891634821891785,
+      "learning_rate": 9.297297297297299e-05,
+      "loss": 0.12082140147686005,
+      "num_input_tokens_seen": 100810,
+      "step": 107,
+      "train_runtime": 405.9752,
+      "train_tokens_per_second": 248.316
+    },
+    {
+      "epoch": 0.025562130177514793,
+      "grad_norm": 0.6624342799186707,
+      "learning_rate": 9.18918918918919e-05,
+      "loss": 0.1473795771598816,
+      "num_input_tokens_seen": 101744,
+      "step": 108,
+      "train_runtime": 409.0084,
+      "train_tokens_per_second": 248.758
+    },
+    {
+      "epoch": 0.025798816568047337,
+      "grad_norm": 0.5968036651611328,
+      "learning_rate": 9.081081081081082e-05,
+      "loss": 0.12923751771450043,
+      "num_input_tokens_seen": 102702,
+      "step": 109,
+      "train_runtime": 412.199,
+      "train_tokens_per_second": 249.156
+    },
+    {
+      "epoch": 0.02603550295857988,
+      "grad_norm": 0.5954580307006836,
+      "learning_rate": 8.972972972972973e-05,
+      "loss": 0.1161399856209755,
+      "num_input_tokens_seen": 103672,
+      "step": 110,
+      "train_runtime": 415.3736,
+      "train_tokens_per_second": 249.587
+    },
+    {
+      "epoch": 0.026272189349112424,
+      "grad_norm": 0.6139379739761353,
+      "learning_rate": 8.864864864864866e-05,
+      "loss": 0.12352899461984634,
+      "num_input_tokens_seen": 104598,
+      "step": 111,
+      "train_runtime": 418.3271,
+      "train_tokens_per_second": 250.039
+    },
+    {
+      "epoch": 0.02650887573964497,
+      "grad_norm": 0.7933095097541809,
+      "learning_rate": 8.756756756756758e-05,
+      "loss": 0.1709994524717331,
+      "num_input_tokens_seen": 105580,
+      "step": 112,
+      "train_runtime": 421.3565,
+      "train_tokens_per_second": 250.572
+    },
+    {
+      "epoch": 0.026745562130177515,
+      "grad_norm": 0.7641370892524719,
+      "learning_rate": 8.64864864864865e-05,
+      "loss": 0.13086311519145966,
+      "num_input_tokens_seen": 106444,
+      "step": 113,
+      "train_runtime": 424.4668,
+      "train_tokens_per_second": 250.771
+    },
+    {
+      "epoch": 0.02698224852071006,
+      "grad_norm": 0.7611938118934631,
+      "learning_rate": 8.540540540540541e-05,
+      "loss": 0.16537640988826752,
+      "num_input_tokens_seen": 107454,
+      "step": 114,
+      "train_runtime": 427.5,
+      "train_tokens_per_second": 251.354
+    },
+    {
+      "epoch": 0.027218934911242602,
+      "grad_norm": 0.7495304346084595,
+      "learning_rate": 8.432432432432433e-05,
+      "loss": 0.14228317141532898,
+      "num_input_tokens_seen": 108426,
+      "step": 115,
+      "train_runtime": 430.5035,
+      "train_tokens_per_second": 251.859
+    },
+    {
+      "epoch": 0.02745562130177515,
+      "grad_norm": 1.2078282833099365,
+      "learning_rate": 8.324324324324326e-05,
+      "loss": 0.10530930012464523,
+      "num_input_tokens_seen": 109446,
+      "step": 116,
+      "train_runtime": 433.4964,
+      "train_tokens_per_second": 252.473
+    },
+    {
+      "epoch": 0.027692307692307693,
+      "grad_norm": 0.6765572428703308,
+      "learning_rate": 8.216216216216217e-05,
+      "loss": 0.10717278718948364,
+      "num_input_tokens_seen": 110374,
+      "step": 117,
+      "train_runtime": 436.5901,
+      "train_tokens_per_second": 252.809
+    },
+    {
+      "epoch": 0.027928994082840237,
+      "grad_norm": 0.8501551151275635,
+      "learning_rate": 8.108108108108109e-05,
+      "loss": 0.17784273624420166,
+      "num_input_tokens_seen": 111340,
+      "step": 118,
+      "train_runtime": 439.6526,
+      "train_tokens_per_second": 253.245
+    },
+    {
+      "epoch": 0.02816568047337278,
+      "grad_norm": 0.7583926320075989,
+      "learning_rate": 8e-05,
+      "loss": 0.16588062047958374,
+      "num_input_tokens_seen": 112288,
+      "step": 119,
+      "train_runtime": 442.8046,
+      "train_tokens_per_second": 253.584
+    },
+    {
+      "epoch": 0.028402366863905324,
+      "grad_norm": 0.6620173454284668,
+      "learning_rate": 7.891891891891892e-05,
+      "loss": 0.11676295101642609,
+      "num_input_tokens_seen": 113206,
+      "step": 120,
+      "train_runtime": 445.9682,
+      "train_tokens_per_second": 253.843
+    }
+  ],
+  "logging_steps": 1,
+  "max_steps": 190,
+  "num_input_tokens_seen": 113206,
+  "num_train_epochs": 1,
+  "save_steps": 30,
+  "stateful_callbacks": {
+    "TrainerControl": {
+      "args": {
+        "should_epoch_stop": false,
+        "should_evaluate": false,
+        "should_log": false,
+        "should_save": true,
+        "should_training_stop": false
+      },
+      "attributes": {}
+    }
+  },
+  "total_flos": 1632037070282880.0,
+  "train_batch_size": 2,
+  "trial_name": null,
+  "trial_params": null
+}

checkpoint-120/training_args.bin

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:34c4ca6d50f04301fb38588516a91421e14a8ad1ffddf12afdfd9ba35cd4b64e
+size 5777

checkpoint-150/README.md

@@ -0,0 +1,210 @@
+---
+base_model: unsloth/gemma-4-e2b-it-unsloth-bnb-4bit
+library_name: peft
+pipeline_tag: text-generation
+tags:
+- base_model:adapter:unsloth/gemma-4-e2b-it-unsloth-bnb-4bit
+- lora
+- sft
+- transformers
+- trl
+- unsloth
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **Developed by:** [More Information Needed]
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed]
+- **Finetuned from model [optional]:** [More Information Needed]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[More Information Needed]
+
+### Downstream Use [optional]
+
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+
+[More Information Needed]
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+[More Information Needed]
+
+## Training Details
+
+### Training Data
+
+<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+
+[More Information Needed]
+
+### Training Procedure
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
+- **Compute Region:** [More Information Needed]
+- **Carbon Emitted:** [More Information Needed]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]
+### Framework versions
+
+- PEFT 0.18.1

checkpoint-150/adapter_config.json

@@ -0,0 +1,50 @@
+{
+  "alora_invocation_tokens": null,
+  "alpha_pattern": {},
+  "arrow_config": null,
+  "auto_mapping": {
+    "base_model_class": "Gemma4ForConditionalGeneration",
+    "parent_library": "transformers.models.gemma4.modeling_gemma4",
+    "unsloth_fixed": true
+  },
+  "base_model_name_or_path": "unsloth/gemma-4-e2b-it-unsloth-bnb-4bit",
+  "bias": "none",
+  "corda_config": null,
+  "ensure_weight_tying": false,
+  "eva_config": null,
+  "exclude_modules": null,
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layer_replication": null,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 32,
+  "lora_bias": false,
+  "lora_dropout": 0.0,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "peft_version": "0.18.1",
+  "qalora_group_size": 16,
+  "r": 16,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "q_proj",
+    "gate_proj",
+    "v_proj",
+    "k_proj",
+    "down_proj",
+    "o_proj",
+    "up_proj"
+  ],
+  "target_parameters": null,
+  "task_type": "CAUSAL_LM",
+  "trainable_token_indices": null,
+  "use_dora": false,
+  "use_qalora": false,
+  "use_rslora": false
+}

checkpoint-150/adapter_model.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:79025ee3acf1d35d8aa435821bda964bc6b3cb6801665ea77bdff85aaa1067c2
+size 124277728

checkpoint-150/chat_template.jinja

@@ -0,0 +1,351 @@
+{%- macro format_parameters(properties, required, filter_keys=false) -%}
+    {%- set standard_keys = ['description', 'type', 'properties', 'required', 'nullable'] -%}
+    {%- set ns = namespace(found_first=false) -%}
+    {%- for key, value in properties | dictsort -%}
+        {%- set add_comma = false -%}
+        {%- if not filter_keys or key not in standard_keys -%}
+            {%- if ns.found_first %},{% endif -%}
+            {%- set ns.found_first = true -%}
+            {{ key }}:{
+            {%- if value['description'] -%}
+                description:<|"|>{{ value['description'] }}<|"|>
+                {%- set add_comma = true -%}
+            {%- endif -%}
+            {%- if value['type'] | upper == 'STRING' -%}
+                {%- if value['enum'] -%}
+                    {%- if add_comma %},{%- else -%} {%- set add_comma = true -%} {% endif -%}
+                    enum:{{ format_argument(value['enum']) }}
+                {%- endif -%}
+            {%- elif value['type'] | upper == 'ARRAY' -%}
+                {%- if value['items'] is mapping and value['items'] -%}
+                    {%- if add_comma %},{%- else -%} {%- set add_comma = true -%} {% endif -%}
+                    items:{
+                    {%- set ns_items = namespace(found_first=false) -%}
+                    {%- for item_key, item_value in value['items'] | dictsort -%}
+                        {%- if item_value is not none -%}
+                            {%- if ns_items.found_first %},{% endif -%}
+                            {%- set ns_items.found_first = true -%}
+                            {%- if item_key == 'properties' -%}
+                                properties:{
+                                {%- if item_value is mapping -%}
+                                    {{- format_parameters(item_value, value['items']['required'] | default([])) -}}
+                                {%- endif -%}
+                                }
+                            {%- elif item_key == 'required' -%}
+                                required:[
+                                {%- for req_item in item_value -%}
+                                    <|"|>{{- req_item -}}<|"|>
+                                    {%- if not loop.last %},{% endif -%}
+                                {%- endfor -%}
+                                ]
+                            {%- elif item_key == 'type' -%}
+                                {%- if item_value is string -%}
+                                    type:{{ format_argument(item_value | upper) }}
+                                {%- else -%}
+                                    type:{{ format_argument(item_value | map('upper') | list) }}
+                                {%- endif -%}
+                            {%- else -%}
+                                {{ item_key }}:{{ format_argument(item_value) }}
+                            {%- endif -%}
+                        {%- endif -%}
+                    {%- endfor -%}
+                    }
+                {%- endif -%}
+            {%- endif -%}
+            {%- if value['nullable'] %}
+                {%- if add_comma %},{%- else -%} {%- set add_comma = true -%} {% endif -%}
+                nullable:true
+            {%- endif -%}
+            {%- if value['type'] | upper == 'OBJECT' -%}
+                {%- if value['properties'] is defined and value['properties'] is mapping -%}
+                    {%- if add_comma %},{%- else -%} {%- set add_comma = true -%} {% endif -%}
+                    properties:{
+                    {{- format_parameters(value['properties'], value['required'] | default([])) -}}
+                    }
+                {%- elif value is mapping -%}
+                    {%- if add_comma %},{%- else -%} {%- set add_comma = true -%} {% endif -%}
+                    properties:{
+                    {{- format_parameters(value, value['required'] | default([]), filter_keys=true) -}}
+                    }
+                {%- endif -%}
+                {%- if value['required'] -%}
+                    {%- if add_comma %},{%- else -%} {%- set add_comma = true -%} {% endif -%}
+                    required:[
+                    {%- for item in value['required'] | default([]) -%}
+                        <|"|>{{- item -}}<|"|>
+                        {%- if not loop.last %},{% endif -%}
+                    {%- endfor -%}
+                    ]
+                {%- endif -%}
+            {%- endif -%}
+            {%- if add_comma %},{%- else -%} {%- set add_comma = true -%} {% endif -%}
+            type:<|"|>{{ value['type'] | upper }}<|"|>}
+        {%- endif -%}
+    {%- endfor -%}
+{%- endmacro -%}
+{%- macro format_function_declaration(tool_data) -%}
+    declaration:{{- tool_data['function']['name'] -}}{description:<|"|>{{- tool_data['function']['description'] -}}<|"|>
+    {%- set params = tool_data['function']['parameters'] -%}
+    {%- if params -%}
+        ,parameters:{
+        {%- if params['properties'] -%}
+            properties:{ {{- format_parameters(params['properties'], params['required']) -}} },
+        {%- endif -%}
+        {%- if params['required'] -%}
+            required:[
+            {%- for item in params['required'] -%}
+                <|"|>{{- item -}}<|"|>
+                {{- ',' if not loop.last -}}
+            {%- endfor -%}
+            ],
+        {%- endif -%}
+        {%- if params['type'] -%}
+            type:<|"|>{{- params['type'] | upper -}}<|"|>}
+        {%- endif -%}
+    {%- endif -%}
+    {%- if 'response' in tool_data['function'] -%}
+        {%- set response_declaration = tool_data['function']['response'] -%}
+        ,response:{
+        {%- if response_declaration['description'] -%}
+            description:<|"|>{{- response_declaration['description'] -}}<|"|>,
+        {%- endif -%}
+        {%- if response_declaration['type'] | upper == 'OBJECT' -%}
+            type:<|"|>{{- response_declaration['type'] | upper -}}<|"|>}
+        {%- endif -%}
+    {%- endif -%}
+    }
+{%- endmacro -%}
+{%- macro format_argument(argument, escape_keys=True) -%}
+    {%- if argument is string -%}
+        {{- '<|"|>' + argument + '<|"|>' -}}
+    {%- elif argument is boolean -%}
+        {{- 'true' if argument else 'false' -}}
+    {%- elif argument is mapping -%}
+        {{- '{' -}}
+        {%- set ns = namespace(found_first=false) -%}
+        {%- for key, value in argument | dictsort -%}
+            {%- if ns.found_first %},{% endif -%}
+            {%- set ns.found_first = true -%}
+            {%- if escape_keys -%}
+                {{- '<|"|>' + key + '<|"|>' -}}
+            {%- else -%}
+                {{- key -}}
+            {%- endif -%}
+            :{{- format_argument(value, escape_keys=escape_keys) -}}
+        {%- endfor -%}
+        {{- '}' -}}
+    {%- elif argument is sequence -%}
+        {{- '[' -}}
+        {%- for item in argument -%}
+            {{- format_argument(item, escape_keys=escape_keys) -}}
+            {%- if not loop.last %},{% endif -%}
+        {%- endfor -%}
+        {{- ']' -}}
+    {%- else -%}
+        {{- argument -}}
+    {%- endif -%}
+{%- endmacro -%}
+{%- macro strip_thinking(text) -%}
+    {%- set ns = namespace(result='') -%}
+    {%- for part in text.split('<channel|>') -%}
+        {%- if '<|channel>' in part -%}
+            {%- set ns.result = ns.result + part.split('<|channel>')[0] -%}
+        {%- else -%}
+            {%- set ns.result = ns.result + part -%}
+        {%- endif -%}
+    {%- endfor -%}
+    {{- ns.result | trim -}}
+{%- endmacro -%}
+
+{%- macro format_tool_response_block(tool_name, response) -%}
+    {{- '<|tool_response>' -}}
+    {%- if response is mapping -%}
+        {{- 'response:' + tool_name + '{' -}}
+        {%- for key, value in response | dictsort -%}
+            {{- key -}}:{{- format_argument(value, escape_keys=False) -}}
+            {%- if not loop.last %},{% endif -%}
+        {%- endfor -%}
+        {{- '}' -}}
+    {%- else -%}
+        {{- 'response:' + tool_name + '{value:' + format_argument(response, escape_keys=False) + '}' -}}
+    {%- endif -%}
+    {{- '<tool_response|>' -}}
+{%- endmacro -%}
+
+{%- set ns = namespace(prev_message_type=None) -%}
+{%- set loop_messages = messages -%}
+{{- bos_token -}}
+{#- Handle System/Tool Definitions Block -#}
+{%- if (enable_thinking is defined and enable_thinking) or tools or messages[0]['role'] in ['system', 'developer'] -%}
+    {{- '<|turn>system\n' -}}
+    {#- Inject Thinking token at the very top of the FIRST system turn -#}
+    {%- if enable_thinking is defined and enable_thinking -%}
+        {{- '<|think|>\n' -}}
+        {%- set ns.prev_message_type = 'think' -%}
+    {%- endif -%}
+    {%- if messages[0]['role'] in ['system', 'developer'] -%}
+        {%- if messages[0]['content'] is string -%}
+            {{- messages[0]['content'] | trim -}}
+        {%- elif messages[0]['content'] is sequence -%}
+            {%- for item in messages[0]['content'] -%}
+                {{- item['text'] | trim + ' '-}}
+            {%- endfor -%}
+        {%- endif -%}
+        {%- set loop_messages = messages[1:] -%}
+    {%- endif -%}
+    {%- if tools -%}
+        {%- for tool in tools %}
+            {{- '<|tool>' -}}
+            {{- format_function_declaration(tool) | trim -}}
+            {{- '<tool|>' -}}
+        {%- endfor %}
+        {%- set ns.prev_message_type = 'tool' -%}
+    {%- endif -%}
+    {{- '<turn|>\n' -}}
+{%- endif %}
+
+{#- Pre-scan: find last user message index for reasoning guard -#}
+{%- set ns_turn = namespace(last_user_idx=-1) -%}
+{%- for i in range(loop_messages | length) -%}
+    {%- if loop_messages[i]['role'] == 'user' -%}
+        {%- set ns_turn.last_user_idx = i -%}
+    {%- endif -%}
+{%- endfor -%}
+
+{#- Loop through messages -#}
+{%- for message in loop_messages -%}
+    {%- if message['role'] != 'tool' -%}
+    {%- set ns.prev_message_type = None -%}
+    {%- set role = 'model' if message['role'] == 'assistant' else message['role'] -%}
+    {#- Detect continuation: suppress duplicate <|turn>model when previous non-tool message was also assistant -#}
+    {%- set prev_nt = namespace(role=None, found=false) -%}
+    {%- if loop.index0 > 0 -%}
+        {%- for j in range(loop.index0 - 1, -1, -1) -%}
+            {%- if not prev_nt.found -%}
+                {%- if loop_messages[j]['role'] != 'tool' -%}
+                    {%- set prev_nt.role = loop_messages[j]['role'] -%}
+                    {%- set prev_nt.found = true -%}
+                {%- endif -%}
+            {%- endif -%}
+        {%- endfor -%}
+    {%- endif -%}
+    {%- set continue_same_model_turn = (role == 'model' and prev_nt.role == 'assistant') -%}
+    {%- if not continue_same_model_turn -%}
+        {{- '<|turn>' + role + '\n' }}
+    {%- endif -%}
+
+    {#- Render reasoning/reasoning_content as thinking channel -#}
+    {%- set thinking_text = message.get('reasoning') or message.get('reasoning_content') -%}
+    {%- if thinking_text and loop.index0 > ns_turn.last_user_idx and message.get('tool_calls') -%}
+        {{- '<|channel>thought\n' + thinking_text + '\n<channel|>' -}}
+    {%- endif -%}
+
+            {%- if message['tool_calls'] -%}
+                {%- for tool_call in message['tool_calls'] -%}
+                    {%- set function = tool_call['function'] -%}
+                    {{- '<|tool_call>call:' + function['name'] + '{' -}}
+                    {%- if function['arguments'] is mapping -%}
+                        {%- set ns_args = namespace(found_first=false) -%}
+                        {%- for key, value in function['arguments'] | dictsort -%}
+                            {%- if ns_args.found_first %},{% endif -%}
+                            {%- set ns_args.found_first = true -%}
+                            {{- key -}}:{{- format_argument(value, escape_keys=False) -}}
+                        {%- endfor -%}
+                    {%- elif function['arguments'] is string -%}
+                        {{- function['arguments'] -}}
+                    {%- endif -%}
+                    {{- '}<tool_call|>' -}}
+                {%- endfor -%}
+                {%- set ns.prev_message_type = 'tool_call' -%}
+            {%- endif -%}
+
+            {%- set ns_tr_out = namespace(flag=false) -%}
+            {%- if message.get('tool_responses') -%}
+                {#- Legacy: tool_responses embedded on the assistant message (Google/Gemma native) -#}
+                {%- for tool_response in message['tool_responses'] -%}
+                    {{- format_tool_response_block(tool_response['name'] | default('unknown'), tool_response['response']) -}}
+                    {%- set ns_tr_out.flag = true -%}
+                    {%- set ns.prev_message_type = 'tool_response' -%}
+                {%- endfor -%}
+            {%- elif message.get('tool_calls') -%}
+                {#- OpenAI Chat Completions: forward-scan consecutive role:tool messages -#}
+                {%- set ns_tool_scan = namespace(stopped=false) -%}
+                {%- for k in range(loop.index0 + 1, loop_messages | length) -%}
+                    {%- if ns_tool_scan.stopped -%}
+                    {%- elif loop_messages[k]['role'] != 'tool' -%}
+                        {%- set ns_tool_scan.stopped = true -%}
+                    {%- else -%}
+                        {%- set follow = loop_messages[k] -%}
+                        {#- Resolve tool_call_id to function name -#}
+                        {%- set ns_tname = namespace(name=follow.get('name') | default('unknown')) -%}
+                        {%- for tc in message['tool_calls'] -%}
+                            {%- if tc.get('id') == follow.get('tool_call_id') -%}
+                                {%- set ns_tname.name = tc['function']['name'] -%}
+                            {%- endif -%}
+                        {%- endfor -%}
+                        {#- Handle content as string or content-parts array -#}
+                        {%- set tool_body = follow.get('content') -%}
+                        {%- if tool_body is string -%}
+                            {{- format_tool_response_block(ns_tname.name, tool_body) -}}
+                        {%- elif tool_body is sequence and tool_body is not string -%}
+                            {%- set ns_txt = namespace(s='') -%}
+                            {%- for part in tool_body -%}
+                                {%- if part.get('type') == 'text' -%}
+                                    {%- set ns_txt.s = ns_txt.s + (part.get('text') | default('')) -%}
+                                {%- endif -%}
+                            {%- endfor -%}
+                            {{- format_tool_response_block(ns_tname.name, ns_txt.s) -}}
+                        {%- else -%}
+                            {{- format_tool_response_block(ns_tname.name, tool_body) -}}
+                        {%- endif -%}
+                        {%- set ns_tr_out.flag = true -%}
+                        {%- set ns.prev_message_type = 'tool_response' -%}
+                    {%- endif -%}
+                {%- endfor -%}
+            {%- endif -%}
+
+            {%- set captured_content -%}
+            {%- if message['content'] is string -%}
+                {%- if role == 'model' -%}
+                    {{- strip_thinking(message['content']) -}}
+                {%- else -%}
+                    {{- message['content'] | trim -}}
+                {%- endif -%}
+            {%- elif message['content'] is sequence -%}
+                {%- for item in message['content'] -%}
+                    {%- if item['type'] == 'text' -%}
+                        {%- if role == 'model' -%}
+                            {{- strip_thinking(item['text']) -}}
+                        {%- else -%}
+                            {{- item['text'] | trim -}}
+                        {%- endif -%}
+                    {%- elif item['type'] == 'image' -%}
+                        {{- '<|image|>' -}}
+                        {%- set ns.prev_message_type = 'image' -%}
+                    {%- elif item['type'] == 'audio' -%}
+                        {{- '<|audio|>' -}}
+                        {%- set ns.prev_message_type = 'audio' -%}
+                    {%- elif item['type'] == 'video' -%}
+                        {{- '<|video|>' -}}
+                        {%- set ns.prev_message_type = 'video' -%}
+                    {%- endif -%}
+                {%- endfor -%}
+            {%- endif -%}
+            {%- endset -%}
+
+            {{- captured_content -}}
+            {%- set has_content = captured_content | trim | length > 0 -%}
+
+        {%- if ns.prev_message_type == 'tool_call' and not ns_tr_out.flag -%}
+            {{- '<|tool_response>' -}}
+        {%- elif not (ns_tr_out.flag and not has_content) -%}
+            {{- '<turn|>\n' -}}
+        {%- endif -%}
+    {%- endif -%}
+{%- endfor -%}
+
+{%- if add_generation_prompt -%}
+    {%- if ns.prev_message_type != 'tool_response' and ns.prev_message_type != 'tool_call' -%}
+        {{- '<|turn>model\n' -}}
+    {%- endif -%}
+{%- endif -%}

checkpoint-150/optimizer.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:676e7ff5f1af2f689ece698e6985cdaf684ab2bafbeeaa8681977a6453dffe22
+size 52047117

checkpoint-150/processor_config.json

@@ -0,0 +1,75 @@
+{
+  "audio_ms_per_token": 40,
+  "audio_seq_length": 750,
+  "feature_extractor": {
+    "dither": 0.0,
+    "feature_extractor_type": "Gemma4AudioFeatureExtractor",
+    "feature_size": 128,
+    "fft_length": 512,
+    "fft_overdrive": false,
+    "frame_length": 320,
+    "hop_length": 160,
+    "input_scale_factor": 1.0,
+    "max_frequency": 8000.0,
+    "mel_floor": 0.001,
+    "min_frequency": 0.0,
+    "padding_side": "left",
+    "padding_value": 0.0,
+    "per_bin_mean": null,
+    "per_bin_stddev": null,
+    "preemphasis": 0.0,
+    "preemphasis_htk_flavor": true,
+    "return_attention_mask": true,
+    "sampling_rate": 16000
+  },
+  "image_processor": {
+    "do_convert_rgb": true,
+    "do_normalize": false,
+    "do_rescale": true,
+    "do_resize": true,
+    "image_mean": [
+      0.0,
+      0.0,
+      0.0
+    ],
+    "image_processor_type": "Gemma4ImageProcessor",
+    "image_seq_length": 280,
+    "image_std": [
+      1.0,
+      1.0,
+      1.0
+    ],
+    "max_soft_tokens": 280,
+    "patch_size": 16,
+    "pooling_kernel_size": 3,
+    "resample": 3,
+    "rescale_factor": 0.00392156862745098
+  },
+  "image_seq_length": 280,
+  "processor_class": "Gemma4Processor",
+  "video_processor": {
+    "do_convert_rgb": true,
+    "do_normalize": true,
+    "do_rescale": true,
+    "do_resize": true,
+    "do_sample_frames": true,
+    "image_mean": [
+      0.0,
+      0.0,
+      0.0
+    ],
+    "image_std": [
+      1.0,
+      1.0,
+      1.0
+    ],
+    "max_soft_tokens": 70,
+    "num_frames": 32,
+    "patch_size": 16,
+    "pooling_kernel_size": 3,
+    "resample": 3,
+    "rescale_factor": 0.00392156862745098,
+    "return_metadata": false,
+    "video_processor_type": "Gemma4VideoProcessor"
+  }
+}

checkpoint-150/rng_state.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:f1d565802a8e26c4e8a31328752b7a7fdc186d9401aa008e65697d0ad8c22e33
+size 14645

checkpoint-150/scaler.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:41ce6f17608f83ea4a19655ee2f08447977bad8cf4b831826d8c03f86b5176e9
+size 1383

checkpoint-150/scheduler.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:a02bbb7a0dfd9017bf6ee57d7f39ecba548a46e11e466823a59cfab4c980712f
+size 1465

checkpoint-150/tokenizer.json

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:cc8d3a0ce36466ccc1278bf987df5f71db1719b9ca6b4118264f45cb627bfe0f
+size 32169626

checkpoint-150/tokenizer_config.json

@@ -0,0 +1,289 @@
+{
+  "audio_token": "<|audio|>",
+  "backend": "tokenizers",
+  "boa_token": "<|audio>",
+  "boi_token": "<|image>",
+  "bos_token": "<bos>",
+  "eoa_token": "<audio|>",
+  "eoc_token": "<channel|>",
+  "eoi_token": "<image|>",
+  "eos_token": "<eos>",
+  "eot_token": "<turn|>",
+  "escape_token": "<|\"|>",
+  "etc_token": "<tool_call|>",
+  "etd_token": "<tool|>",
+  "etr_token": "<tool_response|>",
+  "extra_special_tokens": [
+    "<|video|>"
+  ],
+  "image_token": "<|image|>",
+  "is_local": false,
+  "mask_token": "<mask>",
+  "model_max_length": 131072,
+  "model_specific_special_tokens": {
+    "audio_token": "<|audio|>",
+    "boa_token": "<|audio>",
+    "boi_token": "<|image>",
+    "eoa_token": "<audio|>",
+    "eoc_token": "<channel|>",
+    "eoi_token": "<image|>",
+    "eot_token": "<turn|>",
+    "escape_token": "<|\"|>",
+    "etc_token": "<tool_call|>",
+    "etd_token": "<tool|>",
+    "etr_token": "<tool_response|>",
+    "image_token": "<|image|>",
+    "soc_token": "<|channel>",
+    "sot_token": "<|turn>",
+    "stc_token": "<|tool_call>",
+    "std_token": "<|tool>",
+    "str_token": "<|tool_response>",
+    "think_token": "<|think|>"
+  },
+  "pad_token": "<pad>",
+  "padding_side": "right",
+  "processor_class": "Gemma4Processor",
+  "response_schema": {
+    "properties": {
+      "content": {
+        "type": "string"
+      },
+      "role": {
+        "const": "assistant"
+      },
+      "thinking": {
+        "type": "string"
+      },
+      "tool_calls": {
+        "items": {
+          "properties": {
+            "function": {
+              "properties": {
+                "arguments": {
+                  "additionalProperties": {},
+                  "type": "object",
+                  "x-parser": "gemma4-tool-call"
+                },
+                "name": {
+                  "type": "string"
+                }
+              },
+              "type": "object",
+              "x-regex": "call\\:(?P<name>\\w+)(?P<arguments>\\{.*\\})"
+            },
+            "type": {
+              "const": "function"
+            }
+          },
+          "type": "object"
+        },
+        "type": "array",
+        "x-regex-iterator": "<\\|tool_call>(.*?)<tool_call\\|>"
+      }
+    },
+    "type": "object",
+    "x-regex": "(\\<\\|channel\\>thought\\n(?P<thinking>.*?)\\<channel\\|\\>)?(?P<tool_calls>\\<\\|tool_call\\>.*\\<tool_call\\|\\>)?(?P<content>(?:(?!\\<turn\\|\\>)(?!\\<\\|tool_response\\>).)+)?(?:\\<turn\\|\\>|\\<\\|tool_response\\>)?"
+  },
+  "soc_token": "<|channel>",
+  "sot_token": "<|turn>",
+  "stc_token": "<|tool_call>",
+  "std_token": "<|tool>",
+  "str_token": "<|tool_response>",
+  "think_token": "<|think|>",
+  "tokenizer_class": "GemmaTokenizer",
+  "unk_token": "<unk>",
+  "added_tokens_decoder": {
+    "0": {
+      "content": "<pad>",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    },
+    "1": {
+      "content": "<eos>",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    },
+    "2": {
+      "content": "<bos>",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    },
+    "3": {
+      "content": "<unk>",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    },
+    "4": {
+      "content": "<mask>",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    },
+    "46": {
+      "content": "<|tool>",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    },
+    "47": {
+      "content": "<tool|>",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    },
+    "48": {
+      "content": "<|tool_call>",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    },
+    "49": {
+      "content": "<tool_call|>",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    },
+    "50": {
+      "content": "<|tool_response>",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    },
+    "51": {
+      "content": "<tool_response|>",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    },
+    "52": {
+      "content": "<|\"|>",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    },
+    "98": {
+      "content": "<|think|>",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    },
+    "100": {
+      "content": "<|channel>",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    },
+    "101": {
+      "content": "<channel|>",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    },
+    "105": {
+      "content": "<|turn>",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    },
+    "106": {
+      "content": "<turn|>",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    },
+    "255999": {
+      "content": "<|image>",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    },
+    "256000": {
+      "content": "<|audio>",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    },
+    "258880": {
+      "content": "<|image|>",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    },
+    "258881": {
+      "content": "<|audio|>",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    },
+    "258882": {
+      "content": "<image|>",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    },
+    "258883": {
+      "content": "<audio|>",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    },
+    "258884": {
+      "content": "<|video|>",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    }
+  }
+}

checkpoint-150/trainer_state.json

@@ -0,0 +1,1534 @@
+{
+  "best_global_step": null,
+  "best_metric": null,
+  "best_model_checkpoint": null,
+  "epoch": 0.03550295857988166,
+  "eval_steps": 500,
+  "global_step": 150,
+  "is_hyper_param_search": false,
+  "is_local_process_zero": true,
+  "is_world_process_zero": true,
+  "log_history": [
+    {
+      "epoch": 0.00023668639053254438,
+      "grad_norm": NaN,
+      "learning_rate": 0.0,
+      "loss": 4.347962379455566,
+      "num_input_tokens_seen": 842,
+      "step": 1,
+      "train_runtime": 63.0289,
+      "train_tokens_per_second": 13.359
+    },
+    {
+      "epoch": 0.00047337278106508875,
+      "grad_norm": NaN,
+      "learning_rate": 0.0,
+      "loss": 4.634688854217529,
+      "num_input_tokens_seen": 1820,
+      "step": 2,
+      "train_runtime": 67.7033,
+      "train_tokens_per_second": 26.882
+    },
+    {
+      "epoch": 0.0007100591715976331,
+      "grad_norm": 13.944212913513184,
+      "learning_rate": 0.0,
+      "loss": 4.42241096496582,
+      "num_input_tokens_seen": 2754,
+      "step": 3,
+      "train_runtime": 72.324,
+      "train_tokens_per_second": 38.079
+    },
+    {
+      "epoch": 0.0009467455621301775,
+      "grad_norm": 13.445413589477539,
+      "learning_rate": 4e-05,
+      "loss": 4.682804107666016,
+      "num_input_tokens_seen": 3700,
+      "step": 4,
+      "train_runtime": 75.3925,
+      "train_tokens_per_second": 49.077
+    },
+    {
+      "epoch": 0.001183431952662722,
+      "grad_norm": 10.576727867126465,
+      "learning_rate": 8e-05,
+      "loss": 4.166159629821777,
+      "num_input_tokens_seen": 4714,
+      "step": 5,
+      "train_runtime": 78.474,
+      "train_tokens_per_second": 60.071
+    },
+    {
+      "epoch": 0.0014201183431952662,
+      "grad_norm": 8.077850341796875,
+      "learning_rate": 0.00012,
+      "loss": 3.2006261348724365,
+      "num_input_tokens_seen": 5674,
+      "step": 6,
+      "train_runtime": 81.6139,
+      "train_tokens_per_second": 69.522
+    },
+    {
+      "epoch": 0.0016568047337278107,
+      "grad_norm": 6.60789680480957,
+      "learning_rate": 0.00016,
+      "loss": 2.7067415714263916,
+      "num_input_tokens_seen": 6646,
+      "step": 7,
+      "train_runtime": 84.786,
+      "train_tokens_per_second": 78.386
+    },
+    {
+      "epoch": 0.001893491124260355,
+      "grad_norm": 9.175209045410156,
+      "learning_rate": 0.0002,
+      "loss": 2.367570638656616,
+      "num_input_tokens_seen": 7518,
+      "step": 8,
+      "train_runtime": 87.8178,
+      "train_tokens_per_second": 85.609
+    },
+    {
+      "epoch": 0.0021301775147928993,
+      "grad_norm": 3.438948631286621,
+      "learning_rate": 0.00019891891891891895,
+      "loss": 2.1013119220733643,
+      "num_input_tokens_seen": 8470,
+      "step": 9,
+      "train_runtime": 90.9458,
+      "train_tokens_per_second": 93.132
+    },
+    {
+      "epoch": 0.002366863905325444,
+      "grad_norm": 3.459472894668579,
+      "learning_rate": 0.00019783783783783784,
+      "loss": 1.8991940021514893,
+      "num_input_tokens_seen": 9458,
+      "step": 10,
+      "train_runtime": 94.0577,
+      "train_tokens_per_second": 100.555
+    },
+    {
+      "epoch": 0.0026035502958579883,
+      "grad_norm": 2.169750928878784,
+      "learning_rate": 0.00019675675675675678,
+      "loss": 1.7395055294036865,
+      "num_input_tokens_seen": 10456,
+      "step": 11,
+      "train_runtime": 97.2068,
+      "train_tokens_per_second": 107.565
+    },
+    {
+      "epoch": 0.0028402366863905324,
+      "grad_norm": 1.8638927936553955,
+      "learning_rate": 0.00019567567567567567,
+      "loss": 1.5622950792312622,
+      "num_input_tokens_seen": 11410,
+      "step": 12,
+      "train_runtime": 100.2911,
+      "train_tokens_per_second": 113.769
+    },
+    {
+      "epoch": 0.003076923076923077,
+      "grad_norm": 1.4741116762161255,
+      "learning_rate": 0.00019459459459459462,
+      "loss": 1.392699956893921,
+      "num_input_tokens_seen": 12316,
+      "step": 13,
+      "train_runtime": 103.3664,
+      "train_tokens_per_second": 119.149
+    },
+    {
+      "epoch": 0.0033136094674556214,
+      "grad_norm": 1.3238699436187744,
+      "learning_rate": 0.00019351351351351353,
+      "loss": 1.2535074949264526,
+      "num_input_tokens_seen": 13256,
+      "step": 14,
+      "train_runtime": 106.4031,
+      "train_tokens_per_second": 124.583
+    },
+    {
+      "epoch": 0.0035502958579881655,
+      "grad_norm": 1.276484489440918,
+      "learning_rate": 0.00019243243243243245,
+      "loss": 1.135048508644104,
+      "num_input_tokens_seen": 14228,
+      "step": 15,
+      "train_runtime": 109.4909,
+      "train_tokens_per_second": 129.947
+    },
+    {
+      "epoch": 0.00378698224852071,
+      "grad_norm": 1.1560865640640259,
+      "learning_rate": 0.00019135135135135137,
+      "loss": 1.0317097902297974,
+      "num_input_tokens_seen": 15192,
+      "step": 16,
+      "train_runtime": 112.5741,
+      "train_tokens_per_second": 134.951
+    },
+    {
+      "epoch": 0.004023668639053254,
+      "grad_norm": 1.1331353187561035,
+      "learning_rate": 0.00019027027027027028,
+      "loss": 0.9967219233512878,
+      "num_input_tokens_seen": 16130,
+      "step": 17,
+      "train_runtime": 115.6495,
+      "train_tokens_per_second": 139.473
+    },
+    {
+      "epoch": 0.004260355029585799,
+      "grad_norm": 1.1567702293395996,
+      "learning_rate": 0.0001891891891891892,
+      "loss": 0.905368447303772,
+      "num_input_tokens_seen": 17078,
+      "step": 18,
+      "train_runtime": 118.6796,
+      "train_tokens_per_second": 143.9
+    },
+    {
+      "epoch": 0.004497041420118343,
+      "grad_norm": 0.9157600998878479,
+      "learning_rate": 0.00018810810810810814,
+      "loss": 0.8075690865516663,
+      "num_input_tokens_seen": 18062,
+      "step": 19,
+      "train_runtime": 121.8602,
+      "train_tokens_per_second": 148.219
+    },
+    {
+      "epoch": 0.004733727810650888,
+      "grad_norm": 0.8306605815887451,
+      "learning_rate": 0.00018702702702702703,
+      "loss": 0.8007175922393799,
+      "num_input_tokens_seen": 19078,
+      "step": 20,
+      "train_runtime": 125.0019,
+      "train_tokens_per_second": 152.622
+    },
+    {
+      "epoch": 0.004970414201183432,
+      "grad_norm": 0.690018355846405,
+      "learning_rate": 0.00018594594594594597,
+      "loss": 0.7810791730880737,
+      "num_input_tokens_seen": 20068,
+      "step": 21,
+      "train_runtime": 128.0932,
+      "train_tokens_per_second": 156.667
+    },
+    {
+      "epoch": 0.005207100591715977,
+      "grad_norm": 1.4768867492675781,
+      "learning_rate": 0.00018486486486486486,
+      "loss": 0.7172120809555054,
+      "num_input_tokens_seen": 20972,
+      "step": 22,
+      "train_runtime": 131.0901,
+      "train_tokens_per_second": 159.982
+    },
+    {
+      "epoch": 0.00544378698224852,
+      "grad_norm": 0.7999809980392456,
+      "learning_rate": 0.0001837837837837838,
+      "loss": 0.6333726048469543,
+      "num_input_tokens_seen": 21900,
+      "step": 23,
+      "train_runtime": 134.212,
+      "train_tokens_per_second": 163.175
+    },
+    {
+      "epoch": 0.005680473372781065,
+      "grad_norm": 0.9285996556282043,
+      "learning_rate": 0.00018270270270270272,
+      "loss": 0.6750729084014893,
+      "num_input_tokens_seen": 22770,
+      "step": 24,
+      "train_runtime": 137.3193,
+      "train_tokens_per_second": 165.818
+    },
+    {
+      "epoch": 0.005917159763313609,
+      "grad_norm": 0.7733820080757141,
+      "learning_rate": 0.00018162162162162164,
+      "loss": 0.672032356262207,
+      "num_input_tokens_seen": 23746,
+      "step": 25,
+      "train_runtime": 140.3175,
+      "train_tokens_per_second": 169.23
+    },
+    {
+      "epoch": 0.006153846153846154,
+      "grad_norm": 0.73944091796875,
+      "learning_rate": 0.00018054054054054055,
+      "loss": 0.6716101169586182,
+      "num_input_tokens_seen": 24716,
+      "step": 26,
+      "train_runtime": 143.3683,
+      "train_tokens_per_second": 172.395
+    },
+    {
+      "epoch": 0.006390532544378698,
+      "grad_norm": 0.7659372091293335,
+      "learning_rate": 0.00017945945945945947,
+      "loss": 0.6067175269126892,
+      "num_input_tokens_seen": 25724,
+      "step": 27,
+      "train_runtime": 146.5377,
+      "train_tokens_per_second": 175.545
+    },
+    {
+      "epoch": 0.006627218934911243,
+      "grad_norm": 0.5428617000579834,
+      "learning_rate": 0.00017837837837837839,
+      "loss": 0.6083395481109619,
+      "num_input_tokens_seen": 26712,
+      "step": 28,
+      "train_runtime": 149.6429,
+      "train_tokens_per_second": 178.505
+    },
+    {
+      "epoch": 0.006863905325443787,
+      "grad_norm": 0.5915114283561707,
+      "learning_rate": 0.00017729729729729733,
+      "loss": 0.6463742256164551,
+      "num_input_tokens_seen": 27704,
+      "step": 29,
+      "train_runtime": 152.7501,
+      "train_tokens_per_second": 181.368
+    },
+    {
+      "epoch": 0.007100591715976331,
+      "grad_norm": 1.3350757360458374,
+      "learning_rate": 0.00017621621621621622,
+      "loss": 0.5705698132514954,
+      "num_input_tokens_seen": 28648,
+      "step": 30,
+      "train_runtime": 155.8918,
+      "train_tokens_per_second": 183.768
+    },
+    {
+      "epoch": 0.0073372781065088755,
+      "grad_norm": 0.68421471118927,
+      "learning_rate": 0.00017513513513513516,
+      "loss": 0.5660746097564697,
+      "num_input_tokens_seen": 29622,
+      "step": 31,
+      "train_runtime": 163.3209,
+      "train_tokens_per_second": 181.373
+    },
+    {
+      "epoch": 0.00757396449704142,
+      "grad_norm": 0.5762604475021362,
+      "learning_rate": 0.00017405405405405405,
+      "loss": 0.5483309030532837,
+      "num_input_tokens_seen": 30534,
+      "step": 32,
+      "train_runtime": 166.5185,
+      "train_tokens_per_second": 183.367
+    },
+    {
+      "epoch": 0.0078106508875739646,
+      "grad_norm": 0.5751784443855286,
+      "learning_rate": 0.000172972972972973,
+      "loss": 0.5207005739212036,
+      "num_input_tokens_seen": 31458,
+      "step": 33,
+      "train_runtime": 169.7055,
+      "train_tokens_per_second": 185.368
+    },
+    {
+      "epoch": 0.008047337278106508,
+      "grad_norm": 0.5752039551734924,
+      "learning_rate": 0.0001718918918918919,
+      "loss": 0.5534584522247314,
+      "num_input_tokens_seen": 32424,
+      "step": 34,
+      "train_runtime": 172.9184,
+      "train_tokens_per_second": 187.51
+    },
+    {
+      "epoch": 0.008284023668639054,
+      "grad_norm": 0.5918363332748413,
+      "learning_rate": 0.00017081081081081083,
+      "loss": 0.482683002948761,
+      "num_input_tokens_seen": 33398,
+      "step": 35,
+      "train_runtime": 176.2158,
+      "train_tokens_per_second": 189.529
+    },
+    {
+      "epoch": 0.008520710059171597,
+      "grad_norm": 0.6921846270561218,
+      "learning_rate": 0.00016972972972972974,
+      "loss": 0.46112507581710815,
+      "num_input_tokens_seen": 34324,
+      "step": 36,
+      "train_runtime": 179.3173,
+      "train_tokens_per_second": 191.415
+    },
+    {
+      "epoch": 0.008757396449704143,
+      "grad_norm": 0.6429721117019653,
+      "learning_rate": 0.00016864864864864866,
+      "loss": 0.45629197359085083,
+      "num_input_tokens_seen": 35270,
+      "step": 37,
+      "train_runtime": 182.3558,
+      "train_tokens_per_second": 193.413
+    },
+    {
+      "epoch": 0.008994082840236686,
+      "grad_norm": 0.5477020740509033,
+      "learning_rate": 0.00016756756756756757,
+      "loss": 0.4547877907752991,
+      "num_input_tokens_seen": 36206,
+      "step": 38,
+      "train_runtime": 185.4483,
+      "train_tokens_per_second": 195.235
+    },
+    {
+      "epoch": 0.009230769230769232,
+      "grad_norm": 0.6158634424209595,
+      "learning_rate": 0.00016648648648648652,
+      "loss": 0.367482990026474,
+      "num_input_tokens_seen": 37080,
+      "step": 39,
+      "train_runtime": 188.5114,
+      "train_tokens_per_second": 196.699
+    },
+    {
+      "epoch": 0.009467455621301775,
+      "grad_norm": 0.5405091643333435,
+      "learning_rate": 0.0001654054054054054,
+      "loss": 0.42049410939216614,
+      "num_input_tokens_seen": 38030,
+      "step": 40,
+      "train_runtime": 191.5986,
+      "train_tokens_per_second": 198.488
+    },
+    {
+      "epoch": 0.009704142011834319,
+      "grad_norm": 0.6389183402061462,
+      "learning_rate": 0.00016432432432432435,
+      "loss": 0.3935014307498932,
+      "num_input_tokens_seen": 38942,
+      "step": 41,
+      "train_runtime": 194.8426,
+      "train_tokens_per_second": 199.864
+    },
+    {
+      "epoch": 0.009940828402366864,
+      "grad_norm": 0.6742956042289734,
+      "learning_rate": 0.00016324324324324324,
+      "loss": 0.4373692274093628,
+      "num_input_tokens_seen": 39902,
+      "step": 42,
+      "train_runtime": 197.8938,
+      "train_tokens_per_second": 201.633
+    },
+    {
+      "epoch": 0.010177514792899408,
+      "grad_norm": 0.6083794236183167,
+      "learning_rate": 0.00016216216216216218,
+      "loss": 0.3776765465736389,
+      "num_input_tokens_seen": 40858,
+      "step": 43,
+      "train_runtime": 200.9708,
+      "train_tokens_per_second": 203.303
+    },
+    {
+      "epoch": 0.010414201183431953,
+      "grad_norm": 0.5469992160797119,
+      "learning_rate": 0.0001610810810810811,
+      "loss": 0.31133151054382324,
+      "num_input_tokens_seen": 41760,
+      "step": 44,
+      "train_runtime": 204.1304,
+      "train_tokens_per_second": 204.575
+    },
+    {
+      "epoch": 0.010650887573964497,
+      "grad_norm": 0.6452498435974121,
+      "learning_rate": 0.00016,
+      "loss": 0.42721521854400635,
+      "num_input_tokens_seen": 42740,
+      "step": 45,
+      "train_runtime": 207.1845,
+      "train_tokens_per_second": 206.29
+    },
+    {
+      "epoch": 0.01088757396449704,
+      "grad_norm": 0.5988945960998535,
+      "learning_rate": 0.00015891891891891893,
+      "loss": 0.41375258564949036,
+      "num_input_tokens_seen": 43750,
+      "step": 46,
+      "train_runtime": 210.2912,
+      "train_tokens_per_second": 208.045
+    },
+    {
+      "epoch": 0.011124260355029586,
+      "grad_norm": 0.6452038288116455,
+      "learning_rate": 0.00015783783783783785,
+      "loss": 0.3485276699066162,
+      "num_input_tokens_seen": 44690,
+      "step": 47,
+      "train_runtime": 213.3684,
+      "train_tokens_per_second": 209.45
+    },
+    {
+      "epoch": 0.01136094674556213,
+      "grad_norm": 0.7041454911231995,
+      "learning_rate": 0.00015675675675675676,
+      "loss": 0.3296637535095215,
+      "num_input_tokens_seen": 45666,
+      "step": 48,
+      "train_runtime": 216.4459,
+      "train_tokens_per_second": 210.981
+    },
+    {
+      "epoch": 0.011597633136094675,
+      "grad_norm": 0.6726324558258057,
+      "learning_rate": 0.0001556756756756757,
+      "loss": 0.3179457187652588,
+      "num_input_tokens_seen": 46560,
+      "step": 49,
+      "train_runtime": 219.4697,
+      "train_tokens_per_second": 212.148
+    },
+    {
+      "epoch": 0.011834319526627219,
+      "grad_norm": 0.7513703107833862,
+      "learning_rate": 0.0001545945945945946,
+      "loss": 0.3722391426563263,
+      "num_input_tokens_seen": 47528,
+      "step": 50,
+      "train_runtime": 222.596,
+      "train_tokens_per_second": 213.517
+    },
+    {
+      "epoch": 0.012071005917159764,
+      "grad_norm": 0.6454160213470459,
+      "learning_rate": 0.00015351351351351354,
+      "loss": 0.283376544713974,
+      "num_input_tokens_seen": 48468,
+      "step": 51,
+      "train_runtime": 225.7262,
+      "train_tokens_per_second": 214.72
+    },
+    {
+      "epoch": 0.012307692307692308,
+      "grad_norm": 0.9116244316101074,
+      "learning_rate": 0.00015243243243243243,
+      "loss": 0.4286752939224243,
+      "num_input_tokens_seen": 49444,
+      "step": 52,
+      "train_runtime": 228.803,
+      "train_tokens_per_second": 216.099
+    },
+    {
+      "epoch": 0.012544378698224851,
+      "grad_norm": 0.6157099604606628,
+      "learning_rate": 0.00015135135135135137,
+      "loss": 0.27355721592903137,
+      "num_input_tokens_seen": 50424,
+      "step": 53,
+      "train_runtime": 231.8413,
+      "train_tokens_per_second": 217.494
+    },
+    {
+      "epoch": 0.012781065088757397,
+      "grad_norm": 0.6335808038711548,
+      "learning_rate": 0.00015027027027027028,
+      "loss": 0.37197017669677734,
+      "num_input_tokens_seen": 51328,
+      "step": 54,
+      "train_runtime": 234.9265,
+      "train_tokens_per_second": 218.485
+    },
+    {
+      "epoch": 0.01301775147928994,
+      "grad_norm": 0.6838424205780029,
+      "learning_rate": 0.0001491891891891892,
+      "loss": 0.3504602909088135,
+      "num_input_tokens_seen": 52274,
+      "step": 55,
+      "train_runtime": 238.0114,
+      "train_tokens_per_second": 219.628
+    },
+    {
+      "epoch": 0.013254437869822486,
+      "grad_norm": 0.6566418409347534,
+      "learning_rate": 0.00014810810810810812,
+      "loss": 0.3189927935600281,
+      "num_input_tokens_seen": 53214,
+      "step": 56,
+      "train_runtime": 241.0892,
+      "train_tokens_per_second": 220.723
+    },
+    {
+      "epoch": 0.01349112426035503,
+      "grad_norm": 0.6112971901893616,
+      "learning_rate": 0.00014702702702702703,
+      "loss": 0.3080369830131531,
+      "num_input_tokens_seen": 54162,
+      "step": 57,
+      "train_runtime": 244.2461,
+      "train_tokens_per_second": 221.752
+    },
+    {
+      "epoch": 0.013727810650887575,
+      "grad_norm": 0.6469757556915283,
+      "learning_rate": 0.00014594594594594595,
+      "loss": 0.24279898405075073,
+      "num_input_tokens_seen": 55158,
+      "step": 58,
+      "train_runtime": 247.4064,
+      "train_tokens_per_second": 222.945
+    },
+    {
+      "epoch": 0.013964497041420118,
+      "grad_norm": 0.7099384665489197,
+      "learning_rate": 0.0001448648648648649,
+      "loss": 0.31188705563545227,
+      "num_input_tokens_seen": 56096,
+      "step": 59,
+      "train_runtime": 250.4708,
+      "train_tokens_per_second": 223.962
+    },
+    {
+      "epoch": 0.014201183431952662,
+      "grad_norm": 0.5927040576934814,
+      "learning_rate": 0.00014378378378378378,
+      "loss": 0.25696688890457153,
+      "num_input_tokens_seen": 57012,
+      "step": 60,
+      "train_runtime": 253.7131,
+      "train_tokens_per_second": 224.711
+    },
+    {
+      "epoch": 0.014437869822485207,
+      "grad_norm": 0.5483338236808777,
+      "learning_rate": 0.00014270270270270272,
+      "loss": 0.2725352644920349,
+      "num_input_tokens_seen": 58036,
+      "step": 61,
+      "train_runtime": 260.2844,
+      "train_tokens_per_second": 222.971
+    },
+    {
+      "epoch": 0.014674556213017751,
+      "grad_norm": 0.6806847453117371,
+      "learning_rate": 0.00014162162162162161,
+      "loss": 0.31959983706474304,
+      "num_input_tokens_seen": 59026,
+      "step": 62,
+      "train_runtime": 263.3802,
+      "train_tokens_per_second": 224.109
+    },
+    {
+      "epoch": 0.014911242603550296,
+      "grad_norm": 0.6916660070419312,
+      "learning_rate": 0.00014054054054054056,
+      "loss": 0.312305748462677,
+      "num_input_tokens_seen": 59982,
+      "step": 63,
+      "train_runtime": 266.3794,
+      "train_tokens_per_second": 225.175
+    },
+    {
+      "epoch": 0.01514792899408284,
+      "grad_norm": 0.5516266226768494,
+      "learning_rate": 0.00013945945945945947,
+      "loss": 0.2653953433036804,
+      "num_input_tokens_seen": 60926,
+      "step": 64,
+      "train_runtime": 269.3893,
+      "train_tokens_per_second": 226.163
+    },
+    {
+      "epoch": 0.015384615384615385,
+      "grad_norm": 0.5579270720481873,
+      "learning_rate": 0.0001383783783783784,
+      "loss": 0.20462818443775177,
+      "num_input_tokens_seen": 61844,
+      "step": 65,
+      "train_runtime": 272.3982,
+      "train_tokens_per_second": 227.035
+    },
+    {
+      "epoch": 0.015621301775147929,
+      "grad_norm": 0.7645660638809204,
+      "learning_rate": 0.0001372972972972973,
+      "loss": 0.2650893032550812,
+      "num_input_tokens_seen": 62766,
+      "step": 66,
+      "train_runtime": 275.404,
+      "train_tokens_per_second": 227.905
+    },
+    {
+      "epoch": 0.015857988165680473,
+      "grad_norm": 0.5974738001823425,
+      "learning_rate": 0.00013621621621621622,
+      "loss": 0.21247778832912445,
+      "num_input_tokens_seen": 63690,
+      "step": 67,
+      "train_runtime": 278.4021,
+      "train_tokens_per_second": 228.77
+    },
+    {
+      "epoch": 0.016094674556213016,
+      "grad_norm": 0.5831193327903748,
+      "learning_rate": 0.00013513513513513514,
+      "loss": 0.2024172842502594,
+      "num_input_tokens_seen": 64496,
+      "step": 68,
+      "train_runtime": 281.4313,
+      "train_tokens_per_second": 229.171
+    },
+    {
+      "epoch": 0.016331360946745564,
+      "grad_norm": 0.8678795695304871,
+      "learning_rate": 0.00013405405405405408,
+      "loss": 0.31490638852119446,
+      "num_input_tokens_seen": 65460,
+      "step": 69,
+      "train_runtime": 284.6137,
+      "train_tokens_per_second": 229.996
+    },
+    {
+      "epoch": 0.016568047337278107,
+      "grad_norm": 0.7611344456672668,
+      "learning_rate": 0.00013297297297297297,
+      "loss": 0.24661925435066223,
+      "num_input_tokens_seen": 66374,
+      "step": 70,
+      "train_runtime": 287.7742,
+      "train_tokens_per_second": 230.646
+    },
+    {
+      "epoch": 0.01680473372781065,
+      "grad_norm": 0.6685308814048767,
+      "learning_rate": 0.0001318918918918919,
+      "loss": 0.1843535602092743,
+      "num_input_tokens_seen": 67112,
+      "step": 71,
+      "train_runtime": 290.9321,
+      "train_tokens_per_second": 230.679
+    },
+    {
+      "epoch": 0.017041420118343194,
+      "grad_norm": 0.6150883436203003,
+      "learning_rate": 0.0001308108108108108,
+      "loss": 0.23372295498847961,
+      "num_input_tokens_seen": 68154,
+      "step": 72,
+      "train_runtime": 294.0809,
+      "train_tokens_per_second": 231.753
+    },
+    {
+      "epoch": 0.017278106508875738,
+      "grad_norm": 0.6938812732696533,
+      "learning_rate": 0.00012972972972972974,
+      "loss": 0.22619186341762543,
+      "num_input_tokens_seen": 69102,
+      "step": 73,
+      "train_runtime": 297.1843,
+      "train_tokens_per_second": 232.522
+    },
+    {
+      "epoch": 0.017514792899408285,
+      "grad_norm": 0.617787778377533,
+      "learning_rate": 0.00012864864864864866,
+      "loss": 0.2535328269004822,
+      "num_input_tokens_seen": 70010,
+      "step": 74,
+      "train_runtime": 300.2851,
+      "train_tokens_per_second": 233.145
+    },
+    {
+      "epoch": 0.01775147928994083,
+      "grad_norm": 0.6884900331497192,
+      "learning_rate": 0.00012756756756756758,
+      "loss": 0.21632739901542664,
+      "num_input_tokens_seen": 70940,
+      "step": 75,
+      "train_runtime": 303.3533,
+      "train_tokens_per_second": 233.853
+    },
+    {
+      "epoch": 0.017988165680473372,
+      "grad_norm": 0.5782189965248108,
+      "learning_rate": 0.0001264864864864865,
+      "loss": 0.20167675614356995,
+      "num_input_tokens_seen": 71862,
+      "step": 76,
+      "train_runtime": 306.4503,
+      "train_tokens_per_second": 234.498
+    },
+    {
+      "epoch": 0.018224852071005916,
+      "grad_norm": 0.6541483402252197,
+      "learning_rate": 0.0001254054054054054,
+      "loss": 0.23231221735477448,
+      "num_input_tokens_seen": 72812,
+      "step": 77,
+      "train_runtime": 309.5743,
+      "train_tokens_per_second": 235.2
+    },
+    {
+      "epoch": 0.018461538461538463,
+      "grad_norm": 0.7524886727333069,
+      "learning_rate": 0.00012432432432432433,
+      "loss": 0.27632662653923035,
+      "num_input_tokens_seen": 73774,
+      "step": 78,
+      "train_runtime": 312.6963,
+      "train_tokens_per_second": 235.929
+    },
+    {
+      "epoch": 0.018698224852071007,
+      "grad_norm": 0.716282308101654,
+      "learning_rate": 0.00012324324324324327,
+      "loss": 0.2734939754009247,
+      "num_input_tokens_seen": 74716,
+      "step": 79,
+      "train_runtime": 315.7612,
+      "train_tokens_per_second": 236.622
+    },
+    {
+      "epoch": 0.01893491124260355,
+      "grad_norm": 0.7010631561279297,
+      "learning_rate": 0.00012216216216216216,
+      "loss": 0.2774362564086914,
+      "num_input_tokens_seen": 75692,
+      "step": 80,
+      "train_runtime": 318.7983,
+      "train_tokens_per_second": 237.429
+    },
+    {
+      "epoch": 0.019171597633136094,
+      "grad_norm": 0.6561240553855896,
+      "learning_rate": 0.00012108108108108109,
+      "loss": 0.21640686690807343,
+      "num_input_tokens_seen": 76558,
+      "step": 81,
+      "train_runtime": 321.889,
+      "train_tokens_per_second": 237.84
+    },
+    {
+      "epoch": 0.019408284023668638,
+      "grad_norm": 0.5552831888198853,
+      "learning_rate": 0.00012,
+      "loss": 0.21232956647872925,
+      "num_input_tokens_seen": 77408,
+      "step": 82,
+      "train_runtime": 325.0469,
+      "train_tokens_per_second": 238.144
+    },
+    {
+      "epoch": 0.019644970414201185,
+      "grad_norm": 0.5905120372772217,
+      "learning_rate": 0.00011891891891891893,
+      "loss": 0.22443550825119019,
+      "num_input_tokens_seen": 78278,
+      "step": 83,
+      "train_runtime": 328.099,
+      "train_tokens_per_second": 238.58
+    },
+    {
+      "epoch": 0.01988165680473373,
+      "grad_norm": 0.6606366634368896,
+      "learning_rate": 0.00011783783783783784,
+      "loss": 0.2400747388601303,
+      "num_input_tokens_seen": 79262,
+      "step": 84,
+      "train_runtime": 331.1361,
+      "train_tokens_per_second": 239.364
+    },
+    {
+      "epoch": 0.020118343195266272,
+      "grad_norm": 0.6508055329322815,
+      "learning_rate": 0.00011675675675675676,
+      "loss": 0.19072499871253967,
+      "num_input_tokens_seen": 80144,
+      "step": 85,
+      "train_runtime": 334.2158,
+      "train_tokens_per_second": 239.797
+    },
+    {
+      "epoch": 0.020355029585798816,
+      "grad_norm": 0.606562614440918,
+      "learning_rate": 0.00011567567567567568,
+      "loss": 0.20951862633228302,
+      "num_input_tokens_seen": 81108,
+      "step": 86,
+      "train_runtime": 337.3105,
+      "train_tokens_per_second": 240.455
+    },
+    {
+      "epoch": 0.02059171597633136,
+      "grad_norm": 0.6757521629333496,
+      "learning_rate": 0.00011459459459459461,
+      "loss": 0.17614495754241943,
+      "num_input_tokens_seen": 82032,
+      "step": 87,
+      "train_runtime": 340.3438,
+      "train_tokens_per_second": 241.027
+    },
+    {
+      "epoch": 0.020828402366863907,
+      "grad_norm": 0.671481728553772,
+      "learning_rate": 0.00011351351351351351,
+      "loss": 0.1901710331439972,
+      "num_input_tokens_seen": 82954,
+      "step": 88,
+      "train_runtime": 343.4059,
+      "train_tokens_per_second": 241.563
+    },
+    {
+      "epoch": 0.02106508875739645,
+      "grad_norm": 0.5919027924537659,
+      "learning_rate": 0.00011243243243243244,
+      "loss": 0.1563737988471985,
+      "num_input_tokens_seen": 83880,
+      "step": 89,
+      "train_runtime": 346.5125,
+      "train_tokens_per_second": 242.069
+    },
+    {
+      "epoch": 0.021301775147928994,
+      "grad_norm": 0.7108309268951416,
+      "learning_rate": 0.00011135135135135135,
+      "loss": 0.17256894707679749,
+      "num_input_tokens_seen": 84852,
+      "step": 90,
+      "train_runtime": 349.6508,
+      "train_tokens_per_second": 242.676
+    },
+    {
+      "epoch": 0.021538461538461538,
+      "grad_norm": 0.8608420491218567,
+      "learning_rate": 0.00011027027027027029,
+      "loss": 0.1845530867576599,
+      "num_input_tokens_seen": 85820,
+      "step": 91,
+      "train_runtime": 356.267,
+      "train_tokens_per_second": 240.887
+    },
+    {
+      "epoch": 0.02177514792899408,
+      "grad_norm": 0.9677010774612427,
+      "learning_rate": 0.00010918918918918919,
+      "loss": 0.24358105659484863,
+      "num_input_tokens_seen": 86770,
+      "step": 92,
+      "train_runtime": 359.3722,
+      "train_tokens_per_second": 241.449
+    },
+    {
+      "epoch": 0.02201183431952663,
+      "grad_norm": 0.6302966475486755,
+      "learning_rate": 0.00010810810810810812,
+      "loss": 0.18155133724212646,
+      "num_input_tokens_seen": 87736,
+      "step": 93,
+      "train_runtime": 362.5874,
+      "train_tokens_per_second": 241.972
+    },
+    {
+      "epoch": 0.022248520710059172,
+      "grad_norm": 0.7171812653541565,
+      "learning_rate": 0.00010702702702702702,
+      "loss": 0.15349116921424866,
+      "num_input_tokens_seen": 88626,
+      "step": 94,
+      "train_runtime": 365.7055,
+      "train_tokens_per_second": 242.343
+    },
+    {
+      "epoch": 0.022485207100591716,
+      "grad_norm": 0.7326887845993042,
+      "learning_rate": 0.00010594594594594595,
+      "loss": 0.18243758380413055,
+      "num_input_tokens_seen": 89548,
+      "step": 95,
+      "train_runtime": 368.799,
+      "train_tokens_per_second": 242.81
+    },
+    {
+      "epoch": 0.02272189349112426,
+      "grad_norm": 0.6686019897460938,
+      "learning_rate": 0.00010486486486486487,
+      "loss": 0.15622465312480927,
+      "num_input_tokens_seen": 90504,
+      "step": 96,
+      "train_runtime": 371.8404,
+      "train_tokens_per_second": 243.395
+    },
+    {
+      "epoch": 0.022958579881656806,
+      "grad_norm": 0.6306503415107727,
+      "learning_rate": 0.0001037837837837838,
+      "loss": 0.1272117793560028,
+      "num_input_tokens_seen": 91454,
+      "step": 97,
+      "train_runtime": 375.0199,
+      "train_tokens_per_second": 243.864
+    },
+    {
+      "epoch": 0.02319526627218935,
+      "grad_norm": 0.6068493127822876,
+      "learning_rate": 0.0001027027027027027,
+      "loss": 0.1577155441045761,
+      "num_input_tokens_seen": 92466,
+      "step": 98,
+      "train_runtime": 378.0978,
+      "train_tokens_per_second": 244.556
+    },
+    {
+      "epoch": 0.023431952662721894,
+      "grad_norm": 0.7263635993003845,
+      "learning_rate": 0.00010162162162162163,
+      "loss": 0.1845340132713318,
+      "num_input_tokens_seen": 93398,
+      "step": 99,
+      "train_runtime": 381.1358,
+      "train_tokens_per_second": 245.052
+    },
+    {
+      "epoch": 0.023668639053254437,
+      "grad_norm": 0.6466794013977051,
+      "learning_rate": 0.00010054054054054053,
+      "loss": 0.14443959295749664,
+      "num_input_tokens_seen": 94230,
+      "step": 100,
+      "train_runtime": 384.2906,
+      "train_tokens_per_second": 245.205
+    },
+    {
+      "epoch": 0.02390532544378698,
+      "grad_norm": 0.6924043297767639,
+      "learning_rate": 9.945945945945948e-05,
+      "loss": 0.18473166227340698,
+      "num_input_tokens_seen": 95132,
+      "step": 101,
+      "train_runtime": 387.5005,
+      "train_tokens_per_second": 245.502
+    },
+    {
+      "epoch": 0.024142011834319528,
+      "grad_norm": 0.732337236404419,
+      "learning_rate": 9.837837837837839e-05,
+      "loss": 0.16353662312030792,
+      "num_input_tokens_seen": 96080,
+      "step": 102,
+      "train_runtime": 390.584,
+      "train_tokens_per_second": 245.991
+    },
+    {
+      "epoch": 0.02437869822485207,
+      "grad_norm": 0.5956932902336121,
+      "learning_rate": 9.729729729729731e-05,
+      "loss": 0.16359847784042358,
+      "num_input_tokens_seen": 97048,
+      "step": 103,
+      "train_runtime": 393.6474,
+      "train_tokens_per_second": 246.535
+    },
+    {
+      "epoch": 0.024615384615384615,
+      "grad_norm": 0.6137388348579407,
+      "learning_rate": 9.621621621621622e-05,
+      "loss": 0.15779417753219604,
+      "num_input_tokens_seen": 97986,
+      "step": 104,
+      "train_runtime": 396.7042,
+      "train_tokens_per_second": 247.0
+    },
+    {
+      "epoch": 0.02485207100591716,
+      "grad_norm": 0.7936599254608154,
+      "learning_rate": 9.513513513513514e-05,
+      "loss": 0.21357379853725433,
+      "num_input_tokens_seen": 98894,
+      "step": 105,
+      "train_runtime": 399.8228,
+      "train_tokens_per_second": 247.345
+    },
+    {
+      "epoch": 0.025088757396449703,
+      "grad_norm": 0.6574507355690002,
+      "learning_rate": 9.405405405405407e-05,
+      "loss": 0.1685573309659958,
+      "num_input_tokens_seen": 99856,
+      "step": 106,
+      "train_runtime": 402.8867,
+      "train_tokens_per_second": 247.851
+    },
+    {
+      "epoch": 0.02532544378698225,
+      "grad_norm": 0.5891634821891785,
+      "learning_rate": 9.297297297297299e-05,
+      "loss": 0.12082140147686005,
+      "num_input_tokens_seen": 100810,
+      "step": 107,
+      "train_runtime": 405.9752,
+      "train_tokens_per_second": 248.316
+    },
+    {
+      "epoch": 0.025562130177514793,
+      "grad_norm": 0.6624342799186707,
+      "learning_rate": 9.18918918918919e-05,
+      "loss": 0.1473795771598816,
+      "num_input_tokens_seen": 101744,
+      "step": 108,
+      "train_runtime": 409.0084,
+      "train_tokens_per_second": 248.758
+    },
+    {
+      "epoch": 0.025798816568047337,
+      "grad_norm": 0.5968036651611328,
+      "learning_rate": 9.081081081081082e-05,
+      "loss": 0.12923751771450043,
+      "num_input_tokens_seen": 102702,
+      "step": 109,
+      "train_runtime": 412.199,
+      "train_tokens_per_second": 249.156
+    },
+    {
+      "epoch": 0.02603550295857988,
+      "grad_norm": 0.5954580307006836,
+      "learning_rate": 8.972972972972973e-05,
+      "loss": 0.1161399856209755,
+      "num_input_tokens_seen": 103672,
+      "step": 110,
+      "train_runtime": 415.3736,
+      "train_tokens_per_second": 249.587
+    },
+    {
+      "epoch": 0.026272189349112424,
+      "grad_norm": 0.6139379739761353,
+      "learning_rate": 8.864864864864866e-05,
+      "loss": 0.12352899461984634,
+      "num_input_tokens_seen": 104598,
+      "step": 111,
+      "train_runtime": 418.3271,
+      "train_tokens_per_second": 250.039
+    },
+    {
+      "epoch": 0.02650887573964497,
+      "grad_norm": 0.7933095097541809,
+      "learning_rate": 8.756756756756758e-05,
+      "loss": 0.1709994524717331,
+      "num_input_tokens_seen": 105580,
+      "step": 112,
+      "train_runtime": 421.3565,
+      "train_tokens_per_second": 250.572
+    },
+    {
+      "epoch": 0.026745562130177515,
+      "grad_norm": 0.7641370892524719,
+      "learning_rate": 8.64864864864865e-05,
+      "loss": 0.13086311519145966,
+      "num_input_tokens_seen": 106444,
+      "step": 113,
+      "train_runtime": 424.4668,
+      "train_tokens_per_second": 250.771
+    },
+    {
+      "epoch": 0.02698224852071006,
+      "grad_norm": 0.7611938118934631,
+      "learning_rate": 8.540540540540541e-05,
+      "loss": 0.16537640988826752,
+      "num_input_tokens_seen": 107454,
+      "step": 114,
+      "train_runtime": 427.5,
+      "train_tokens_per_second": 251.354
+    },
+    {
+      "epoch": 0.027218934911242602,
+      "grad_norm": 0.7495304346084595,
+      "learning_rate": 8.432432432432433e-05,
+      "loss": 0.14228317141532898,
+      "num_input_tokens_seen": 108426,
+      "step": 115,
+      "train_runtime": 430.5035,
+      "train_tokens_per_second": 251.859
+    },
+    {
+      "epoch": 0.02745562130177515,
+      "grad_norm": 1.2078282833099365,
+      "learning_rate": 8.324324324324326e-05,
+      "loss": 0.10530930012464523,
+      "num_input_tokens_seen": 109446,
+      "step": 116,
+      "train_runtime": 433.4964,
+      "train_tokens_per_second": 252.473
+    },
+    {
+      "epoch": 0.027692307692307693,
+      "grad_norm": 0.6765572428703308,
+      "learning_rate": 8.216216216216217e-05,
+      "loss": 0.10717278718948364,
+      "num_input_tokens_seen": 110374,
+      "step": 117,
+      "train_runtime": 436.5901,
+      "train_tokens_per_second": 252.809
+    },
+    {
+      "epoch": 0.027928994082840237,
+      "grad_norm": 0.8501551151275635,
+      "learning_rate": 8.108108108108109e-05,
+      "loss": 0.17784273624420166,
+      "num_input_tokens_seen": 111340,
+      "step": 118,
+      "train_runtime": 439.6526,
+      "train_tokens_per_second": 253.245
+    },
+    {
+      "epoch": 0.02816568047337278,
+      "grad_norm": 0.7583926320075989,
+      "learning_rate": 8e-05,
+      "loss": 0.16588062047958374,
+      "num_input_tokens_seen": 112288,
+      "step": 119,
+      "train_runtime": 442.8046,
+      "train_tokens_per_second": 253.584
+    },
+    {
+      "epoch": 0.028402366863905324,
+      "grad_norm": 0.6620173454284668,
+      "learning_rate": 7.891891891891892e-05,
+      "loss": 0.11676295101642609,
+      "num_input_tokens_seen": 113206,
+      "step": 120,
+      "train_runtime": 445.9682,
+      "train_tokens_per_second": 253.843
+    },
+    {
+      "epoch": 0.02863905325443787,
+      "grad_norm": 0.6844660639762878,
+      "learning_rate": 7.783783783783785e-05,
+      "loss": 0.09329869598150253,
+      "num_input_tokens_seen": 114134,
+      "step": 121,
+      "train_runtime": 452.5692,
+      "train_tokens_per_second": 252.191
+    },
+    {
+      "epoch": 0.028875739644970415,
+      "grad_norm": 0.7968376874923706,
+      "learning_rate": 7.675675675675677e-05,
+      "loss": 0.13320565223693848,
+      "num_input_tokens_seen": 115088,
+      "step": 122,
+      "train_runtime": 455.6245,
+      "train_tokens_per_second": 252.594
+    },
+    {
+      "epoch": 0.02911242603550296,
+      "grad_norm": 0.8079301118850708,
+      "learning_rate": 7.567567567567568e-05,
+      "loss": 0.1387016326189041,
+      "num_input_tokens_seen": 116006,
+      "step": 123,
+      "train_runtime": 458.7601,
+      "train_tokens_per_second": 252.869
+    },
+    {
+      "epoch": 0.029349112426035502,
+      "grad_norm": 1.1301748752593994,
+      "learning_rate": 7.45945945945946e-05,
+      "loss": 0.197790265083313,
+      "num_input_tokens_seen": 116958,
+      "step": 124,
+      "train_runtime": 461.861,
+      "train_tokens_per_second": 253.232
+    },
+    {
+      "epoch": 0.029585798816568046,
+      "grad_norm": 0.7272042632102966,
+      "learning_rate": 7.351351351351352e-05,
+      "loss": 0.12121891975402832,
+      "num_input_tokens_seen": 117886,
+      "step": 125,
+      "train_runtime": 465.0328,
+      "train_tokens_per_second": 253.5
+    },
+    {
+      "epoch": 0.029822485207100593,
+      "grad_norm": 0.6021063923835754,
+      "learning_rate": 7.243243243243245e-05,
+      "loss": 0.08234579861164093,
+      "num_input_tokens_seen": 118806,
+      "step": 126,
+      "train_runtime": 468.1518,
+      "train_tokens_per_second": 253.777
+    },
+    {
+      "epoch": 0.030059171597633137,
+      "grad_norm": 0.5659137964248657,
+      "learning_rate": 7.135135135135136e-05,
+      "loss": 0.07469362020492554,
+      "num_input_tokens_seen": 119716,
+      "step": 127,
+      "train_runtime": 471.2559,
+      "train_tokens_per_second": 254.036
+    },
+    {
+      "epoch": 0.03029585798816568,
+      "grad_norm": 0.7604466080665588,
+      "learning_rate": 7.027027027027028e-05,
+      "loss": 0.15167035162448883,
+      "num_input_tokens_seen": 120710,
+      "step": 128,
+      "train_runtime": 474.3536,
+      "train_tokens_per_second": 254.473
+    },
+    {
+      "epoch": 0.030532544378698224,
+      "grad_norm": 0.898281455039978,
+      "learning_rate": 6.91891891891892e-05,
+      "loss": 0.18358615040779114,
+      "num_input_tokens_seen": 121668,
+      "step": 129,
+      "train_runtime": 477.4676,
+      "train_tokens_per_second": 254.819
+    },
+    {
+      "epoch": 0.03076923076923077,
+      "grad_norm": 1.046539545059204,
+      "learning_rate": 6.810810810810811e-05,
+      "loss": 0.14173445105552673,
+      "num_input_tokens_seen": 122654,
+      "step": 130,
+      "train_runtime": 480.6242,
+      "train_tokens_per_second": 255.197
+    },
+    {
+      "epoch": 0.031005917159763315,
+      "grad_norm": 0.689860463142395,
+      "learning_rate": 6.702702702702704e-05,
+      "loss": 0.1232977956533432,
+      "num_input_tokens_seen": 123610,
+      "step": 131,
+      "train_runtime": 483.7904,
+      "train_tokens_per_second": 255.503
+    },
+    {
+      "epoch": 0.031242603550295858,
+      "grad_norm": 0.6417210698127747,
+      "learning_rate": 6.594594594594596e-05,
+      "loss": 0.08111131936311722,
+      "num_input_tokens_seen": 124526,
+      "step": 132,
+      "train_runtime": 486.9241,
+      "train_tokens_per_second": 255.74
+    },
+    {
+      "epoch": 0.0314792899408284,
+      "grad_norm": 0.8019670844078064,
+      "learning_rate": 6.486486486486487e-05,
+      "loss": 0.13235916197299957,
+      "num_input_tokens_seen": 125438,
+      "step": 133,
+      "train_runtime": 490.0416,
+      "train_tokens_per_second": 255.974
+    },
+    {
+      "epoch": 0.031715976331360946,
+      "grad_norm": 0.8618372082710266,
+      "learning_rate": 6.378378378378379e-05,
+      "loss": 0.11209192872047424,
+      "num_input_tokens_seen": 126378,
+      "step": 134,
+      "train_runtime": 493.0816,
+      "train_tokens_per_second": 256.302
+    },
+    {
+      "epoch": 0.03195266272189349,
+      "grad_norm": 0.6566123962402344,
+      "learning_rate": 6.27027027027027e-05,
+      "loss": 0.08107412606477737,
+      "num_input_tokens_seen": 127280,
+      "step": 135,
+      "train_runtime": 496.1373,
+      "train_tokens_per_second": 256.542
+    },
+    {
+      "epoch": 0.03218934911242603,
+      "grad_norm": 0.671886682510376,
+      "learning_rate": 6.162162162162163e-05,
+      "loss": 0.10395485162734985,
+      "num_input_tokens_seen": 128246,
+      "step": 136,
+      "train_runtime": 499.2198,
+      "train_tokens_per_second": 256.893
+    },
+    {
+      "epoch": 0.032426035502958576,
+      "grad_norm": 0.5853029489517212,
+      "learning_rate": 6.0540540540540543e-05,
+      "loss": 0.06830425560474396,
+      "num_input_tokens_seen": 129142,
+      "step": 137,
+      "train_runtime": 502.2719,
+      "train_tokens_per_second": 257.116
+    },
+    {
+      "epoch": 0.03266272189349113,
+      "grad_norm": 0.9871621131896973,
+      "learning_rate": 5.9459459459459466e-05,
+      "loss": 0.14138084650039673,
+      "num_input_tokens_seen": 130060,
+      "step": 138,
+      "train_runtime": 505.3687,
+      "train_tokens_per_second": 257.357
+    },
+    {
+      "epoch": 0.03289940828402367,
+      "grad_norm": 0.6716732978820801,
+      "learning_rate": 5.837837837837838e-05,
+      "loss": 0.07525799423456192,
+      "num_input_tokens_seen": 130982,
+      "step": 139,
+      "train_runtime": 508.4248,
+      "train_tokens_per_second": 257.623
+    },
+    {
+      "epoch": 0.033136094674556214,
+      "grad_norm": 0.7177789807319641,
+      "learning_rate": 5.7297297297297305e-05,
+      "loss": 0.09517940878868103,
+      "num_input_tokens_seen": 131900,
+      "step": 140,
+      "train_runtime": 511.57,
+      "train_tokens_per_second": 257.834
+    },
+    {
+      "epoch": 0.03337278106508876,
+      "grad_norm": 0.703551709651947,
+      "learning_rate": 5.621621621621622e-05,
+      "loss": 0.09361469000577927,
+      "num_input_tokens_seen": 132890,
+      "step": 141,
+      "train_runtime": 514.7186,
+      "train_tokens_per_second": 258.18
+    },
+    {
+      "epoch": 0.0336094674556213,
+      "grad_norm": 0.7156357765197754,
+      "learning_rate": 5.5135135135135144e-05,
+      "loss": 0.08832181245088577,
+      "num_input_tokens_seen": 133810,
+      "step": 142,
+      "train_runtime": 517.7644,
+      "train_tokens_per_second": 258.438
+    },
+    {
+      "epoch": 0.033846153846153845,
+      "grad_norm": 0.7757886648178101,
+      "learning_rate": 5.405405405405406e-05,
+      "loss": 0.12478049844503403,
+      "num_input_tokens_seen": 134758,
+      "step": 143,
+      "train_runtime": 520.8215,
+      "train_tokens_per_second": 258.741
+    },
+    {
+      "epoch": 0.03408284023668639,
+      "grad_norm": 0.6047410368919373,
+      "learning_rate": 5.2972972972972976e-05,
+      "loss": 0.07645335048437119,
+      "num_input_tokens_seen": 135724,
+      "step": 144,
+      "train_runtime": 523.9787,
+      "train_tokens_per_second": 259.026
+    },
+    {
+      "epoch": 0.03431952662721893,
+      "grad_norm": 0.7750188708305359,
+      "learning_rate": 5.18918918918919e-05,
+      "loss": 0.10904290527105331,
+      "num_input_tokens_seen": 136662,
+      "step": 145,
+      "train_runtime": 527.0633,
+      "train_tokens_per_second": 259.29
+    },
+    {
+      "epoch": 0.034556213017751476,
+      "grad_norm": 0.6400149464607239,
+      "learning_rate": 5.0810810810810815e-05,
+      "loss": 0.07525563985109329,
+      "num_input_tokens_seen": 137628,
+      "step": 146,
+      "train_runtime": 530.1299,
+      "train_tokens_per_second": 259.612
+    },
+    {
+      "epoch": 0.03479289940828403,
+      "grad_norm": 0.6681646108627319,
+      "learning_rate": 4.972972972972974e-05,
+      "loss": 0.08536849915981293,
+      "num_input_tokens_seen": 138610,
+      "step": 147,
+      "train_runtime": 533.159,
+      "train_tokens_per_second": 259.979
+    },
+    {
+      "epoch": 0.03502958579881657,
+      "grad_norm": 0.6158885359764099,
+      "learning_rate": 4.8648648648648654e-05,
+      "loss": 0.0753958523273468,
+      "num_input_tokens_seen": 139486,
+      "step": 148,
+      "train_runtime": 536.2632,
+      "train_tokens_per_second": 260.107
+    },
+    {
+      "epoch": 0.035266272189349114,
+      "grad_norm": 0.665565550327301,
+      "learning_rate": 4.756756756756757e-05,
+      "loss": 0.08198000490665436,
+      "num_input_tokens_seen": 140440,
+      "step": 149,
+      "train_runtime": 539.3165,
+      "train_tokens_per_second": 260.404
+    },
+    {
+      "epoch": 0.03550295857988166,
+      "grad_norm": 0.6818353533744812,
+      "learning_rate": 4.648648648648649e-05,
+      "loss": 0.0710655227303505,
+      "num_input_tokens_seen": 141344,
+      "step": 150,
+      "train_runtime": 542.3824,
+      "train_tokens_per_second": 260.598
+    }
+  ],
+  "logging_steps": 1,
+  "max_steps": 190,
+  "num_input_tokens_seen": 141344,
+  "num_train_epochs": 1,
+  "save_steps": 30,
+  "stateful_callbacks": {
+    "TrainerControl": {
+      "args": {
+        "should_epoch_stop": false,
+        "should_evaluate": false,
+        "should_log": false,
+        "should_save": true,
+        "should_training_stop": false
+      },
+      "attributes": {}
+    }
+  },
+  "total_flos": 2037689236101120.0,
+  "train_batch_size": 2,
+  "trial_name": null,
+  "trial_params": null
+}

checkpoint-150/training_args.bin

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:34c4ca6d50f04301fb38588516a91421e14a8ad1ffddf12afdfd9ba35cd4b64e
+size 5777

checkpoint-180/README.md

@@ -0,0 +1,210 @@
+---
+base_model: unsloth/gemma-4-e2b-it-unsloth-bnb-4bit
+library_name: peft
+pipeline_tag: text-generation
+tags:
+- base_model:adapter:unsloth/gemma-4-e2b-it-unsloth-bnb-4bit
+- lora
+- sft
+- transformers
+- trl
+- unsloth
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **Developed by:** [More Information Needed]
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed]
+- **Finetuned from model [optional]:** [More Information Needed]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[More Information Needed]
+
+### Downstream Use [optional]
+
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+
+[More Information Needed]
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+[More Information Needed]
+
+## Training Details
+
+### Training Data
+
+<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+
+[More Information Needed]
+
+### Training Procedure
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
+- **Compute Region:** [More Information Needed]
+- **Carbon Emitted:** [More Information Needed]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]
+### Framework versions
+
+- PEFT 0.18.1

checkpoint-180/adapter_config.json

@@ -0,0 +1,50 @@
+{
+  "alora_invocation_tokens": null,
+  "alpha_pattern": {},
+  "arrow_config": null,
+  "auto_mapping": {
+    "base_model_class": "Gemma4ForConditionalGeneration",
+    "parent_library": "transformers.models.gemma4.modeling_gemma4",
+    "unsloth_fixed": true
+  },
+  "base_model_name_or_path": "unsloth/gemma-4-e2b-it-unsloth-bnb-4bit",
+  "bias": "none",
+  "corda_config": null,
+  "ensure_weight_tying": false,
+  "eva_config": null,
+  "exclude_modules": null,
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layer_replication": null,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 32,
+  "lora_bias": false,
+  "lora_dropout": 0.0,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "peft_version": "0.18.1",
+  "qalora_group_size": 16,
+  "r": 16,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "q_proj",
+    "gate_proj",
+    "v_proj",
+    "k_proj",
+    "down_proj",
+    "o_proj",
+    "up_proj"
+  ],
+  "target_parameters": null,
+  "task_type": "CAUSAL_LM",
+  "trainable_token_indices": null,
+  "use_dora": false,
+  "use_qalora": false,
+  "use_rslora": false
+}

checkpoint-180/adapter_model.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:4e2c1029454f1834f511c4c2d3a52d76531655516a9d3045514d762b5156feb6
+size 124277728

checkpoint-180/chat_template.jinja

@@ -0,0 +1,351 @@
+{%- macro format_parameters(properties, required, filter_keys=false) -%}
+    {%- set standard_keys = ['description', 'type', 'properties', 'required', 'nullable'] -%}
+    {%- set ns = namespace(found_first=false) -%}
+    {%- for key, value in properties | dictsort -%}
+        {%- set add_comma = false -%}
+        {%- if not filter_keys or key not in standard_keys -%}
+            {%- if ns.found_first %},{% endif -%}
+            {%- set ns.found_first = true -%}
+            {{ key }}:{
+            {%- if value['description'] -%}
+                description:<|"|>{{ value['description'] }}<|"|>
+                {%- set add_comma = true -%}
+            {%- endif -%}
+            {%- if value['type'] | upper == 'STRING' -%}
+                {%- if value['enum'] -%}
+                    {%- if add_comma %},{%- else -%} {%- set add_comma = true -%} {% endif -%}
+                    enum:{{ format_argument(value['enum']) }}
+                {%- endif -%}
+            {%- elif value['type'] | upper == 'ARRAY' -%}
+                {%- if value['items'] is mapping and value['items'] -%}
+                    {%- if add_comma %},{%- else -%} {%- set add_comma = true -%} {% endif -%}
+                    items:{
+                    {%- set ns_items = namespace(found_first=false) -%}
+                    {%- for item_key, item_value in value['items'] | dictsort -%}
+                        {%- if item_value is not none -%}
+                            {%- if ns_items.found_first %},{% endif -%}
+                            {%- set ns_items.found_first = true -%}
+                            {%- if item_key == 'properties' -%}
+                                properties:{
+                                {%- if item_value is mapping -%}
+                                    {{- format_parameters(item_value, value['items']['required'] | default([])) -}}
+                                {%- endif -%}
+                                }
+                            {%- elif item_key == 'required' -%}
+                                required:[
+                                {%- for req_item in item_value -%}
+                                    <|"|>{{- req_item -}}<|"|>
+                                    {%- if not loop.last %},{% endif -%}
+                                {%- endfor -%}
+                                ]
+                            {%- elif item_key == 'type' -%}
+                                {%- if item_value is string -%}
+                                    type:{{ format_argument(item_value | upper) }}
+                                {%- else -%}
+                                    type:{{ format_argument(item_value | map('upper') | list) }}
+                                {%- endif -%}
+                            {%- else -%}
+                                {{ item_key }}:{{ format_argument(item_value) }}
+                            {%- endif -%}
+                        {%- endif -%}
+                    {%- endfor -%}
+                    }
+                {%- endif -%}
+            {%- endif -%}
+            {%- if value['nullable'] %}
+                {%- if add_comma %},{%- else -%} {%- set add_comma = true -%} {% endif -%}
+                nullable:true
+            {%- endif -%}
+            {%- if value['type'] | upper == 'OBJECT' -%}
+                {%- if value['properties'] is defined and value['properties'] is mapping -%}
+                    {%- if add_comma %},{%- else -%} {%- set add_comma = true -%} {% endif -%}
+                    properties:{
+                    {{- format_parameters(value['properties'], value['required'] | default([])) -}}
+                    }
+                {%- elif value is mapping -%}
+                    {%- if add_comma %},{%- else -%} {%- set add_comma = true -%} {% endif -%}
+                    properties:{
+                    {{- format_parameters(value, value['required'] | default([]), filter_keys=true) -}}
+                    }
+                {%- endif -%}
+                {%- if value['required'] -%}
+                    {%- if add_comma %},{%- else -%} {%- set add_comma = true -%} {% endif -%}
+                    required:[
+                    {%- for item in value['required'] | default([]) -%}
+                        <|"|>{{- item -}}<|"|>
+                        {%- if not loop.last %},{% endif -%}
+                    {%- endfor -%}
+                    ]
+                {%- endif -%}
+            {%- endif -%}
+            {%- if add_comma %},{%- else -%} {%- set add_comma = true -%} {% endif -%}
+            type:<|"|>{{ value['type'] | upper }}<|"|>}
+        {%- endif -%}
+    {%- endfor -%}
+{%- endmacro -%}
+{%- macro format_function_declaration(tool_data) -%}
+    declaration:{{- tool_data['function']['name'] -}}{description:<|"|>{{- tool_data['function']['description'] -}}<|"|>
+    {%- set params = tool_data['function']['parameters'] -%}
+    {%- if params -%}
+        ,parameters:{
+        {%- if params['properties'] -%}
+            properties:{ {{- format_parameters(params['properties'], params['required']) -}} },
+        {%- endif -%}
+        {%- if params['required'] -%}
+            required:[
+            {%- for item in params['required'] -%}
+                <|"|>{{- item -}}<|"|>
+                {{- ',' if not loop.last -}}
+            {%- endfor -%}
+            ],
+        {%- endif -%}
+        {%- if params['type'] -%}
+            type:<|"|>{{- params['type'] | upper -}}<|"|>}
+        {%- endif -%}
+    {%- endif -%}
+    {%- if 'response' in tool_data['function'] -%}
+        {%- set response_declaration = tool_data['function']['response'] -%}
+        ,response:{
+        {%- if response_declaration['description'] -%}
+            description:<|"|>{{- response_declaration['description'] -}}<|"|>,
+        {%- endif -%}
+        {%- if response_declaration['type'] | upper == 'OBJECT' -%}
+            type:<|"|>{{- response_declaration['type'] | upper -}}<|"|>}
+        {%- endif -%}
+    {%- endif -%}
+    }
+{%- endmacro -%}
+{%- macro format_argument(argument, escape_keys=True) -%}
+    {%- if argument is string -%}
+        {{- '<|"|>' + argument + '<|"|>' -}}
+    {%- elif argument is boolean -%}
+        {{- 'true' if argument else 'false' -}}
+    {%- elif argument is mapping -%}
+        {{- '{' -}}
+        {%- set ns = namespace(found_first=false) -%}
+        {%- for key, value in argument | dictsort -%}
+            {%- if ns.found_first %},{% endif -%}
+            {%- set ns.found_first = true -%}
+            {%- if escape_keys -%}
+                {{- '<|"|>' + key + '<|"|>' -}}
+            {%- else -%}
+                {{- key -}}
+            {%- endif -%}
+            :{{- format_argument(value, escape_keys=escape_keys) -}}
+        {%- endfor -%}
+        {{- '}' -}}
+    {%- elif argument is sequence -%}
+        {{- '[' -}}
+        {%- for item in argument -%}
+            {{- format_argument(item, escape_keys=escape_keys) -}}
+            {%- if not loop.last %},{% endif -%}
+        {%- endfor -%}
+        {{- ']' -}}
+    {%- else -%}
+        {{- argument -}}
+    {%- endif -%}
+{%- endmacro -%}
+{%- macro strip_thinking(text) -%}
+    {%- set ns = namespace(result='') -%}
+    {%- for part in text.split('<channel|>') -%}
+        {%- if '<|channel>' in part -%}
+            {%- set ns.result = ns.result + part.split('<|channel>')[0] -%}
+        {%- else -%}
+            {%- set ns.result = ns.result + part -%}
+        {%- endif -%}
+    {%- endfor -%}
+    {{- ns.result | trim -}}
+{%- endmacro -%}
+
+{%- macro format_tool_response_block(tool_name, response) -%}
+    {{- '<|tool_response>' -}}
+    {%- if response is mapping -%}
+        {{- 'response:' + tool_name + '{' -}}
+        {%- for key, value in response | dictsort -%}
+            {{- key -}}:{{- format_argument(value, escape_keys=False) -}}
+            {%- if not loop.last %},{% endif -%}
+        {%- endfor -%}
+        {{- '}' -}}
+    {%- else -%}
+        {{- 'response:' + tool_name + '{value:' + format_argument(response, escape_keys=False) + '}' -}}
+    {%- endif -%}
+    {{- '<tool_response|>' -}}
+{%- endmacro -%}
+
+{%- set ns = namespace(prev_message_type=None) -%}
+{%- set loop_messages = messages -%}
+{{- bos_token -}}
+{#- Handle System/Tool Definitions Block -#}
+{%- if (enable_thinking is defined and enable_thinking) or tools or messages[0]['role'] in ['system', 'developer'] -%}
+    {{- '<|turn>system\n' -}}
+    {#- Inject Thinking token at the very top of the FIRST system turn -#}
+    {%- if enable_thinking is defined and enable_thinking -%}
+        {{- '<|think|>\n' -}}
+        {%- set ns.prev_message_type = 'think' -%}
+    {%- endif -%}
+    {%- if messages[0]['role'] in ['system', 'developer'] -%}
+        {%- if messages[0]['content'] is string -%}
+            {{- messages[0]['content'] | trim -}}
+        {%- elif messages[0]['content'] is sequence -%}
+            {%- for item in messages[0]['content'] -%}
+                {{- item['text'] | trim + ' '-}}
+            {%- endfor -%}
+        {%- endif -%}
+        {%- set loop_messages = messages[1:] -%}
+    {%- endif -%}
+    {%- if tools -%}
+        {%- for tool in tools %}
+            {{- '<|tool>' -}}
+            {{- format_function_declaration(tool) | trim -}}
+            {{- '<tool|>' -}}
+        {%- endfor %}
+        {%- set ns.prev_message_type = 'tool' -%}
+    {%- endif -%}
+    {{- '<turn|>\n' -}}
+{%- endif %}
+
+{#- Pre-scan: find last user message index for reasoning guard -#}
+{%- set ns_turn = namespace(last_user_idx=-1) -%}
+{%- for i in range(loop_messages | length) -%}
+    {%- if loop_messages[i]['role'] == 'user' -%}
+        {%- set ns_turn.last_user_idx = i -%}
+    {%- endif -%}
+{%- endfor -%}
+
+{#- Loop through messages -#}
+{%- for message in loop_messages -%}
+    {%- if message['role'] != 'tool' -%}
+    {%- set ns.prev_message_type = None -%}
+    {%- set role = 'model' if message['role'] == 'assistant' else message['role'] -%}
+    {#- Detect continuation: suppress duplicate <|turn>model when previous non-tool message was also assistant -#}
+    {%- set prev_nt = namespace(role=None, found=false) -%}
+    {%- if loop.index0 > 0 -%}
+        {%- for j in range(loop.index0 - 1, -1, -1) -%}
+            {%- if not prev_nt.found -%}
+                {%- if loop_messages[j]['role'] != 'tool' -%}
+                    {%- set prev_nt.role = loop_messages[j]['role'] -%}
+                    {%- set prev_nt.found = true -%}
+                {%- endif -%}
+            {%- endif -%}
+        {%- endfor -%}
+    {%- endif -%}
+    {%- set continue_same_model_turn = (role == 'model' and prev_nt.role == 'assistant') -%}
+    {%- if not continue_same_model_turn -%}
+        {{- '<|turn>' + role + '\n' }}
+    {%- endif -%}
+
+    {#- Render reasoning/reasoning_content as thinking channel -#}
+    {%- set thinking_text = message.get('reasoning') or message.get('reasoning_content') -%}
+    {%- if thinking_text and loop.index0 > ns_turn.last_user_idx and message.get('tool_calls') -%}
+        {{- '<|channel>thought\n' + thinking_text + '\n<channel|>' -}}
+    {%- endif -%}
+
+            {%- if message['tool_calls'] -%}
+                {%- for tool_call in message['tool_calls'] -%}
+                    {%- set function = tool_call['function'] -%}
+                    {{- '<|tool_call>call:' + function['name'] + '{' -}}
+                    {%- if function['arguments'] is mapping -%}
+                        {%- set ns_args = namespace(found_first=false) -%}
+                        {%- for key, value in function['arguments'] | dictsort -%}
+                            {%- if ns_args.found_first %},{% endif -%}
+                            {%- set ns_args.found_first = true -%}
+                            {{- key -}}:{{- format_argument(value, escape_keys=False) -}}
+                        {%- endfor -%}
+                    {%- elif function['arguments'] is string -%}
+                        {{- function['arguments'] -}}
+                    {%- endif -%}
+                    {{- '}<tool_call|>' -}}
+                {%- endfor -%}
+                {%- set ns.prev_message_type = 'tool_call' -%}
+            {%- endif -%}
+
+            {%- set ns_tr_out = namespace(flag=false) -%}
+            {%- if message.get('tool_responses') -%}
+                {#- Legacy: tool_responses embedded on the assistant message (Google/Gemma native) -#}
+                {%- for tool_response in message['tool_responses'] -%}
+                    {{- format_tool_response_block(tool_response['name'] | default('unknown'), tool_response['response']) -}}
+                    {%- set ns_tr_out.flag = true -%}
+                    {%- set ns.prev_message_type = 'tool_response' -%}
+                {%- endfor -%}
+            {%- elif message.get('tool_calls') -%}
+                {#- OpenAI Chat Completions: forward-scan consecutive role:tool messages -#}
+                {%- set ns_tool_scan = namespace(stopped=false) -%}
+                {%- for k in range(loop.index0 + 1, loop_messages | length) -%}
+                    {%- if ns_tool_scan.stopped -%}
+                    {%- elif loop_messages[k]['role'] != 'tool' -%}
+                        {%- set ns_tool_scan.stopped = true -%}
+                    {%- else -%}
+                        {%- set follow = loop_messages[k] -%}
+                        {#- Resolve tool_call_id to function name -#}
+                        {%- set ns_tname = namespace(name=follow.get('name') | default('unknown')) -%}
+                        {%- for tc in message['tool_calls'] -%}
+                            {%- if tc.get('id') == follow.get('tool_call_id') -%}
+                                {%- set ns_tname.name = tc['function']['name'] -%}
+                            {%- endif -%}
+                        {%- endfor -%}
+                        {#- Handle content as string or content-parts array -#}
+                        {%- set tool_body = follow.get('content') -%}
+                        {%- if tool_body is string -%}
+                            {{- format_tool_response_block(ns_tname.name, tool_body) -}}
+                        {%- elif tool_body is sequence and tool_body is not string -%}
+                            {%- set ns_txt = namespace(s='') -%}
+                            {%- for part in tool_body -%}
+                                {%- if part.get('type') == 'text' -%}
+                                    {%- set ns_txt.s = ns_txt.s + (part.get('text') | default('')) -%}
+                                {%- endif -%}
+                            {%- endfor -%}
+                            {{- format_tool_response_block(ns_tname.name, ns_txt.s) -}}
+                        {%- else -%}
+                            {{- format_tool_response_block(ns_tname.name, tool_body) -}}
+                        {%- endif -%}
+                        {%- set ns_tr_out.flag = true -%}
+                        {%- set ns.prev_message_type = 'tool_response' -%}
+                    {%- endif -%}
+                {%- endfor -%}
+            {%- endif -%}
+
+            {%- set captured_content -%}
+            {%- if message['content'] is string -%}
+                {%- if role == 'model' -%}
+                    {{- strip_thinking(message['content']) -}}
+                {%- else -%}
+                    {{- message['content'] | trim -}}
+                {%- endif -%}
+            {%- elif message['content'] is sequence -%}
+                {%- for item in message['content'] -%}
+                    {%- if item['type'] == 'text' -%}
+                        {%- if role == 'model' -%}
+                            {{- strip_thinking(item['text']) -}}
+                        {%- else -%}
+                            {{- item['text'] | trim -}}
+                        {%- endif -%}
+                    {%- elif item['type'] == 'image' -%}
+                        {{- '<|image|>' -}}
+                        {%- set ns.prev_message_type = 'image' -%}
+                    {%- elif item['type'] == 'audio' -%}
+                        {{- '<|audio|>' -}}
+                        {%- set ns.prev_message_type = 'audio' -%}
+                    {%- elif item['type'] == 'video' -%}
+                        {{- '<|video|>' -}}
+                        {%- set ns.prev_message_type = 'video' -%}
+                    {%- endif -%}
+                {%- endfor -%}
+            {%- endif -%}
+            {%- endset -%}
+
+            {{- captured_content -}}
+            {%- set has_content = captured_content | trim | length > 0 -%}
+
+        {%- if ns.prev_message_type == 'tool_call' and not ns_tr_out.flag -%}
+            {{- '<|tool_response>' -}}
+        {%- elif not (ns_tr_out.flag and not has_content) -%}
+            {{- '<turn|>\n' -}}
+        {%- endif -%}
+    {%- endif -%}
+{%- endfor -%}
+
+{%- if add_generation_prompt -%}
+    {%- if ns.prev_message_type != 'tool_response' and ns.prev_message_type != 'tool_call' -%}
+        {{- '<|turn>model\n' -}}
+    {%- endif -%}
+{%- endif -%}

checkpoint-180/optimizer.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:d28a0dc846feefdc15b5a30c4ff928dcdd8416bb2c13beef4fa5f4ca242bd821
+size 52047117

checkpoint-180/processor_config.json

@@ -0,0 +1,75 @@
+{
+  "audio_ms_per_token": 40,
+  "audio_seq_length": 750,
+  "feature_extractor": {
+    "dither": 0.0,
+    "feature_extractor_type": "Gemma4AudioFeatureExtractor",
+    "feature_size": 128,
+    "fft_length": 512,
+    "fft_overdrive": false,
+    "frame_length": 320,
+    "hop_length": 160,
+    "input_scale_factor": 1.0,
+    "max_frequency": 8000.0,
+    "mel_floor": 0.001,
+    "min_frequency": 0.0,
+    "padding_side": "left",
+    "padding_value": 0.0,
+    "per_bin_mean": null,
+    "per_bin_stddev": null,
+    "preemphasis": 0.0,
+    "preemphasis_htk_flavor": true,
+    "return_attention_mask": true,
+    "sampling_rate": 16000
+  },
+  "image_processor": {
+    "do_convert_rgb": true,
+    "do_normalize": false,
+    "do_rescale": true,
+    "do_resize": true,
+    "image_mean": [
+      0.0,
+      0.0,
+      0.0
+    ],
+    "image_processor_type": "Gemma4ImageProcessor",
+    "image_seq_length": 280,
+    "image_std": [
+      1.0,
+      1.0,
+      1.0
+    ],
+    "max_soft_tokens": 280,
+    "patch_size": 16,
+    "pooling_kernel_size": 3,
+    "resample": 3,
+    "rescale_factor": 0.00392156862745098
+  },
+  "image_seq_length": 280,
+  "processor_class": "Gemma4Processor",
+  "video_processor": {
+    "do_convert_rgb": true,
+    "do_normalize": true,
+    "do_rescale": true,
+    "do_resize": true,
+    "do_sample_frames": true,
+    "image_mean": [
+      0.0,
+      0.0,
+      0.0
+    ],
+    "image_std": [
+      1.0,
+      1.0,
+      1.0
+    ],
+    "max_soft_tokens": 70,
+    "num_frames": 32,
+    "patch_size": 16,
+    "pooling_kernel_size": 3,
+    "resample": 3,
+    "rescale_factor": 0.00392156862745098,
+    "return_metadata": false,
+    "video_processor_type": "Gemma4VideoProcessor"
+  }
+}

checkpoint-180/rng_state.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:f1d565802a8e26c4e8a31328752b7a7fdc186d9401aa008e65697d0ad8c22e33
+size 14645

checkpoint-180/scaler.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:157cc77e7dd6e9c2bce809a6b120c6be65dd2e62a42b62dfda1d462877a40ec3
+size 1383

checkpoint-180/scheduler.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:ec2bd51ad4fa32551317ffe221c08d896ed511f96c24b01b67eb1975b12513fc
+size 1465

checkpoint-180/tokenizer.json

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:cc8d3a0ce36466ccc1278bf987df5f71db1719b9ca6b4118264f45cb627bfe0f
+size 32169626

checkpoint-180/tokenizer_config.json

@@ -0,0 +1,289 @@
+{
+  "audio_token": "<|audio|>",
+  "backend": "tokenizers",
+  "boa_token": "<|audio>",
+  "boi_token": "<|image>",
+  "bos_token": "<bos>",
+  "eoa_token": "<audio|>",
+  "eoc_token": "<channel|>",
+  "eoi_token": "<image|>",
+  "eos_token": "<eos>",
+  "eot_token": "<turn|>",
+  "escape_token": "<|\"|>",
+  "etc_token": "<tool_call|>",
+  "etd_token": "<tool|>",
+  "etr_token": "<tool_response|>",
+  "extra_special_tokens": [
+    "<|video|>"
+  ],
+  "image_token": "<|image|>",
+  "is_local": false,
+  "mask_token": "<mask>",
+  "model_max_length": 131072,
+  "model_specific_special_tokens": {
+    "audio_token": "<|audio|>",
+    "boa_token": "<|audio>",
+    "boi_token": "<|image>",
+    "eoa_token": "<audio|>",
+    "eoc_token": "<channel|>",
+    "eoi_token": "<image|>",
+    "eot_token": "<turn|>",
+    "escape_token": "<|\"|>",
+    "etc_token": "<tool_call|>",
+    "etd_token": "<tool|>",
+    "etr_token": "<tool_response|>",
+    "image_token": "<|image|>",
+    "soc_token": "<|channel>",
+    "sot_token": "<|turn>",
+    "stc_token": "<|tool_call>",
+    "std_token": "<|tool>",
+    "str_token": "<|tool_response>",
+    "think_token": "<|think|>"
+  },
+  "pad_token": "<pad>",
+  "padding_side": "right",
+  "processor_class": "Gemma4Processor",
+  "response_schema": {
+    "properties": {
+      "content": {
+        "type": "string"
+      },
+      "role": {
+        "const": "assistant"
+      },
+      "thinking": {
+        "type": "string"
+      },
+      "tool_calls": {
+        "items": {
+          "properties": {
+            "function": {
+              "properties": {
+                "arguments": {
+                  "additionalProperties": {},
+                  "type": "object",
+                  "x-parser": "gemma4-tool-call"
+                },
+                "name": {
+                  "type": "string"
+                }
+              },
+              "type": "object",
+              "x-regex": "call\\:(?P<name>\\w+)(?P<arguments>\\{.*\\})"
+            },
+            "type": {
+              "const": "function"
+            }
+          },
+          "type": "object"
+        },
+        "type": "array",
+        "x-regex-iterator": "<\\|tool_call>(.*?)<tool_call\\|>"
+      }
+    },
+    "type": "object",
+    "x-regex": "(\\<\\|channel\\>thought\\n(?P<thinking>.*?)\\<channel\\|\\>)?(?P<tool_calls>\\<\\|tool_call\\>.*\\<tool_call\\|\\>)?(?P<content>(?:(?!\\<turn\\|\\>)(?!\\<\\|tool_response\\>).)+)?(?:\\<turn\\|\\>|\\<\\|tool_response\\>)?"
+  },
+  "soc_token": "<|channel>",
+  "sot_token": "<|turn>",
+  "stc_token": "<|tool_call>",
+  "std_token": "<|tool>",
+  "str_token": "<|tool_response>",
+  "think_token": "<|think|>",
+  "tokenizer_class": "GemmaTokenizer",
+  "unk_token": "<unk>",
+  "added_tokens_decoder": {
+    "0": {
+      "content": "<pad>",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    },
+    "1": {
+      "content": "<eos>",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    },
+    "2": {
+      "content": "<bos>",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    },
+    "3": {
+      "content": "<unk>",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    },
+    "4": {
+      "content": "<mask>",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    },
+    "46": {
+      "content": "<|tool>",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    },
+    "47": {
+      "content": "<tool|>",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    },
+    "48": {
+      "content": "<|tool_call>",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    },
+    "49": {
+      "content": "<tool_call|>",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    },
+    "50": {
+      "content": "<|tool_response>",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    },
+    "51": {
+      "content": "<tool_response|>",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    },
+    "52": {
+      "content": "<|\"|>",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    },
+    "98": {
+      "content": "<|think|>",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    },
+    "100": {
+      "content": "<|channel>",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    },
+    "101": {
+      "content": "<channel|>",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    },
+    "105": {
+      "content": "<|turn>",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    },
+    "106": {
+      "content": "<turn|>",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    },
+    "255999": {
+      "content": "<|image>",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    },
+    "256000": {
+      "content": "<|audio>",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    },
+    "258880": {
+      "content": "<|image|>",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    },
+    "258881": {
+      "content": "<|audio|>",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    },
+    "258882": {
+      "content": "<image|>",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    },
+    "258883": {
+      "content": "<audio|>",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    },
+    "258884": {
+      "content": "<|video|>",
+      "single_word": false,
+      "lstrip": false,
+      "rstrip": false,
+      "normalized": false,
+      "special": true
+    }
+  }
+}

checkpoint-180/trainer_state.json

@@ -0,0 +1,1834 @@
+{
+  "best_global_step": null,
+  "best_metric": null,
+  "best_model_checkpoint": null,
+  "epoch": 0.04260355029585799,
+  "eval_steps": 500,
+  "global_step": 180,
+  "is_hyper_param_search": false,
+  "is_local_process_zero": true,
+  "is_world_process_zero": true,
+  "log_history": [
+    {
+      "epoch": 0.00023668639053254438,
+      "grad_norm": NaN,
+      "learning_rate": 0.0,
+      "loss": 4.347962379455566,
+      "num_input_tokens_seen": 842,
+      "step": 1,
+      "train_runtime": 63.0289,
+      "train_tokens_per_second": 13.359
+    },
+    {
+      "epoch": 0.00047337278106508875,
+      "grad_norm": NaN,
+      "learning_rate": 0.0,
+      "loss": 4.634688854217529,
+      "num_input_tokens_seen": 1820,
+      "step": 2,
+      "train_runtime": 67.7033,
+      "train_tokens_per_second": 26.882
+    },
+    {
+      "epoch": 0.0007100591715976331,
+      "grad_norm": 13.944212913513184,
+      "learning_rate": 0.0,
+      "loss": 4.42241096496582,
+      "num_input_tokens_seen": 2754,
+      "step": 3,
+      "train_runtime": 72.324,
+      "train_tokens_per_second": 38.079
+    },
+    {
+      "epoch": 0.0009467455621301775,
+      "grad_norm": 13.445413589477539,
+      "learning_rate": 4e-05,
+      "loss": 4.682804107666016,
+      "num_input_tokens_seen": 3700,
+      "step": 4,
+      "train_runtime": 75.3925,
+      "train_tokens_per_second": 49.077
+    },
+    {
+      "epoch": 0.001183431952662722,
+      "grad_norm": 10.576727867126465,
+      "learning_rate": 8e-05,
+      "loss": 4.166159629821777,
+      "num_input_tokens_seen": 4714,
+      "step": 5,
+      "train_runtime": 78.474,
+      "train_tokens_per_second": 60.071
+    },
+    {
+      "epoch": 0.0014201183431952662,
+      "grad_norm": 8.077850341796875,
+      "learning_rate": 0.00012,
+      "loss": 3.2006261348724365,
+      "num_input_tokens_seen": 5674,
+      "step": 6,
+      "train_runtime": 81.6139,
+      "train_tokens_per_second": 69.522
+    },
+    {
+      "epoch": 0.0016568047337278107,
+      "grad_norm": 6.60789680480957,
+      "learning_rate": 0.00016,
+      "loss": 2.7067415714263916,
+      "num_input_tokens_seen": 6646,
+      "step": 7,
+      "train_runtime": 84.786,
+      "train_tokens_per_second": 78.386
+    },
+    {
+      "epoch": 0.001893491124260355,
+      "grad_norm": 9.175209045410156,
+      "learning_rate": 0.0002,
+      "loss": 2.367570638656616,
+      "num_input_tokens_seen": 7518,
+      "step": 8,
+      "train_runtime": 87.8178,
+      "train_tokens_per_second": 85.609
+    },
+    {
+      "epoch": 0.0021301775147928993,
+      "grad_norm": 3.438948631286621,
+      "learning_rate": 0.00019891891891891895,
+      "loss": 2.1013119220733643,
+      "num_input_tokens_seen": 8470,
+      "step": 9,
+      "train_runtime": 90.9458,
+      "train_tokens_per_second": 93.132
+    },
+    {
+      "epoch": 0.002366863905325444,
+      "grad_norm": 3.459472894668579,
+      "learning_rate": 0.00019783783783783784,
+      "loss": 1.8991940021514893,
+      "num_input_tokens_seen": 9458,
+      "step": 10,
+      "train_runtime": 94.0577,
+      "train_tokens_per_second": 100.555
+    },
+    {
+      "epoch": 0.0026035502958579883,
+      "grad_norm": 2.169750928878784,
+      "learning_rate": 0.00019675675675675678,
+      "loss": 1.7395055294036865,
+      "num_input_tokens_seen": 10456,
+      "step": 11,
+      "train_runtime": 97.2068,
+      "train_tokens_per_second": 107.565
+    },
+    {
+      "epoch": 0.0028402366863905324,
+      "grad_norm": 1.8638927936553955,
+      "learning_rate": 0.00019567567567567567,
+      "loss": 1.5622950792312622,
+      "num_input_tokens_seen": 11410,
+      "step": 12,
+      "train_runtime": 100.2911,
+      "train_tokens_per_second": 113.769
+    },
+    {
+      "epoch": 0.003076923076923077,
+      "grad_norm": 1.4741116762161255,
+      "learning_rate": 0.00019459459459459462,
+      "loss": 1.392699956893921,
+      "num_input_tokens_seen": 12316,
+      "step": 13,
+      "train_runtime": 103.3664,
+      "train_tokens_per_second": 119.149
+    },
+    {
+      "epoch": 0.0033136094674556214,
+      "grad_norm": 1.3238699436187744,
+      "learning_rate": 0.00019351351351351353,
+      "loss": 1.2535074949264526,
+      "num_input_tokens_seen": 13256,
+      "step": 14,
+      "train_runtime": 106.4031,
+      "train_tokens_per_second": 124.583
+    },
+    {
+      "epoch": 0.0035502958579881655,
+      "grad_norm": 1.276484489440918,
+      "learning_rate": 0.00019243243243243245,
+      "loss": 1.135048508644104,
+      "num_input_tokens_seen": 14228,
+      "step": 15,
+      "train_runtime": 109.4909,
+      "train_tokens_per_second": 129.947
+    },
+    {
+      "epoch": 0.00378698224852071,
+      "grad_norm": 1.1560865640640259,
+      "learning_rate": 0.00019135135135135137,
+      "loss": 1.0317097902297974,
+      "num_input_tokens_seen": 15192,
+      "step": 16,
+      "train_runtime": 112.5741,
+      "train_tokens_per_second": 134.951
+    },
+    {
+      "epoch": 0.004023668639053254,
+      "grad_norm": 1.1331353187561035,
+      "learning_rate": 0.00019027027027027028,
+      "loss": 0.9967219233512878,
+      "num_input_tokens_seen": 16130,
+      "step": 17,
+      "train_runtime": 115.6495,
+      "train_tokens_per_second": 139.473
+    },
+    {
+      "epoch": 0.004260355029585799,
+      "grad_norm": 1.1567702293395996,
+      "learning_rate": 0.0001891891891891892,
+      "loss": 0.905368447303772,
+      "num_input_tokens_seen": 17078,
+      "step": 18,
+      "train_runtime": 118.6796,
+      "train_tokens_per_second": 143.9
+    },
+    {
+      "epoch": 0.004497041420118343,
+      "grad_norm": 0.9157600998878479,
+      "learning_rate": 0.00018810810810810814,
+      "loss": 0.8075690865516663,
+      "num_input_tokens_seen": 18062,
+      "step": 19,
+      "train_runtime": 121.8602,
+      "train_tokens_per_second": 148.219
+    },
+    {
+      "epoch": 0.004733727810650888,
+      "grad_norm": 0.8306605815887451,
+      "learning_rate": 0.00018702702702702703,
+      "loss": 0.8007175922393799,
+      "num_input_tokens_seen": 19078,
+      "step": 20,
+      "train_runtime": 125.0019,
+      "train_tokens_per_second": 152.622
+    },
+    {
+      "epoch": 0.004970414201183432,
+      "grad_norm": 0.690018355846405,
+      "learning_rate": 0.00018594594594594597,
+      "loss": 0.7810791730880737,
+      "num_input_tokens_seen": 20068,
+      "step": 21,
+      "train_runtime": 128.0932,
+      "train_tokens_per_second": 156.667
+    },
+    {
+      "epoch": 0.005207100591715977,
+      "grad_norm": 1.4768867492675781,
+      "learning_rate": 0.00018486486486486486,
+      "loss": 0.7172120809555054,
+      "num_input_tokens_seen": 20972,
+      "step": 22,
+      "train_runtime": 131.0901,
+      "train_tokens_per_second": 159.982
+    },
+    {
+      "epoch": 0.00544378698224852,
+      "grad_norm": 0.7999809980392456,
+      "learning_rate": 0.0001837837837837838,
+      "loss": 0.6333726048469543,
+      "num_input_tokens_seen": 21900,
+      "step": 23,
+      "train_runtime": 134.212,
+      "train_tokens_per_second": 163.175
+    },
+    {
+      "epoch": 0.005680473372781065,
+      "grad_norm": 0.9285996556282043,
+      "learning_rate": 0.00018270270270270272,
+      "loss": 0.6750729084014893,
+      "num_input_tokens_seen": 22770,
+      "step": 24,
+      "train_runtime": 137.3193,
+      "train_tokens_per_second": 165.818
+    },
+    {
+      "epoch": 0.005917159763313609,
+      "grad_norm": 0.7733820080757141,
+      "learning_rate": 0.00018162162162162164,
+      "loss": 0.672032356262207,
+      "num_input_tokens_seen": 23746,
+      "step": 25,
+      "train_runtime": 140.3175,
+      "train_tokens_per_second": 169.23
+    },
+    {
+      "epoch": 0.006153846153846154,
+      "grad_norm": 0.73944091796875,
+      "learning_rate": 0.00018054054054054055,
+      "loss": 0.6716101169586182,
+      "num_input_tokens_seen": 24716,
+      "step": 26,
+      "train_runtime": 143.3683,
+      "train_tokens_per_second": 172.395
+    },
+    {
+      "epoch": 0.006390532544378698,
+      "grad_norm": 0.7659372091293335,
+      "learning_rate": 0.00017945945945945947,
+      "loss": 0.6067175269126892,
+      "num_input_tokens_seen": 25724,
+      "step": 27,
+      "train_runtime": 146.5377,
+      "train_tokens_per_second": 175.545
+    },
+    {
+      "epoch": 0.006627218934911243,
+      "grad_norm": 0.5428617000579834,
+      "learning_rate": 0.00017837837837837839,
+      "loss": 0.6083395481109619,
+      "num_input_tokens_seen": 26712,
+      "step": 28,
+      "train_runtime": 149.6429,
+      "train_tokens_per_second": 178.505
+    },
+    {
+      "epoch": 0.006863905325443787,
+      "grad_norm": 0.5915114283561707,
+      "learning_rate": 0.00017729729729729733,
+      "loss": 0.6463742256164551,
+      "num_input_tokens_seen": 27704,
+      "step": 29,
+      "train_runtime": 152.7501,
+      "train_tokens_per_second": 181.368
+    },
+    {
+      "epoch": 0.007100591715976331,
+      "grad_norm": 1.3350757360458374,
+      "learning_rate": 0.00017621621621621622,
+      "loss": 0.5705698132514954,
+      "num_input_tokens_seen": 28648,
+      "step": 30,
+      "train_runtime": 155.8918,
+      "train_tokens_per_second": 183.768
+    },
+    {
+      "epoch": 0.0073372781065088755,
+      "grad_norm": 0.68421471118927,
+      "learning_rate": 0.00017513513513513516,
+      "loss": 0.5660746097564697,
+      "num_input_tokens_seen": 29622,
+      "step": 31,
+      "train_runtime": 163.3209,
+      "train_tokens_per_second": 181.373
+    },
+    {
+      "epoch": 0.00757396449704142,
+      "grad_norm": 0.5762604475021362,
+      "learning_rate": 0.00017405405405405405,
+      "loss": 0.5483309030532837,
+      "num_input_tokens_seen": 30534,
+      "step": 32,
+      "train_runtime": 166.5185,
+      "train_tokens_per_second": 183.367
+    },
+    {
+      "epoch": 0.0078106508875739646,
+      "grad_norm": 0.5751784443855286,
+      "learning_rate": 0.000172972972972973,
+      "loss": 0.5207005739212036,
+      "num_input_tokens_seen": 31458,
+      "step": 33,
+      "train_runtime": 169.7055,
+      "train_tokens_per_second": 185.368
+    },
+    {
+      "epoch": 0.008047337278106508,
+      "grad_norm": 0.5752039551734924,
+      "learning_rate": 0.0001718918918918919,
+      "loss": 0.5534584522247314,
+      "num_input_tokens_seen": 32424,
+      "step": 34,
+      "train_runtime": 172.9184,
+      "train_tokens_per_second": 187.51
+    },
+    {
+      "epoch": 0.008284023668639054,
+      "grad_norm": 0.5918363332748413,
+      "learning_rate": 0.00017081081081081083,
+      "loss": 0.482683002948761,
+      "num_input_tokens_seen": 33398,
+      "step": 35,
+      "train_runtime": 176.2158,
+      "train_tokens_per_second": 189.529
+    },
+    {
+      "epoch": 0.008520710059171597,
+      "grad_norm": 0.6921846270561218,
+      "learning_rate": 0.00016972972972972974,
+      "loss": 0.46112507581710815,
+      "num_input_tokens_seen": 34324,
+      "step": 36,
+      "train_runtime": 179.3173,
+      "train_tokens_per_second": 191.415
+    },
+    {
+      "epoch": 0.008757396449704143,
+      "grad_norm": 0.6429721117019653,
+      "learning_rate": 0.00016864864864864866,
+      "loss": 0.45629197359085083,
+      "num_input_tokens_seen": 35270,
+      "step": 37,
+      "train_runtime": 182.3558,
+      "train_tokens_per_second": 193.413
+    },
+    {
+      "epoch": 0.008994082840236686,
+      "grad_norm": 0.5477020740509033,
+      "learning_rate": 0.00016756756756756757,
+      "loss": 0.4547877907752991,
+      "num_input_tokens_seen": 36206,
+      "step": 38,
+      "train_runtime": 185.4483,
+      "train_tokens_per_second": 195.235
+    },
+    {
+      "epoch": 0.009230769230769232,
+      "grad_norm": 0.6158634424209595,
+      "learning_rate": 0.00016648648648648652,
+      "loss": 0.367482990026474,
+      "num_input_tokens_seen": 37080,
+      "step": 39,
+      "train_runtime": 188.5114,
+      "train_tokens_per_second": 196.699
+    },
+    {
+      "epoch": 0.009467455621301775,
+      "grad_norm": 0.5405091643333435,
+      "learning_rate": 0.0001654054054054054,
+      "loss": 0.42049410939216614,
+      "num_input_tokens_seen": 38030,
+      "step": 40,
+      "train_runtime": 191.5986,
+      "train_tokens_per_second": 198.488
+    },
+    {
+      "epoch": 0.009704142011834319,
+      "grad_norm": 0.6389183402061462,
+      "learning_rate": 0.00016432432432432435,
+      "loss": 0.3935014307498932,
+      "num_input_tokens_seen": 38942,
+      "step": 41,
+      "train_runtime": 194.8426,
+      "train_tokens_per_second": 199.864
+    },
+    {
+      "epoch": 0.009940828402366864,
+      "grad_norm": 0.6742956042289734,
+      "learning_rate": 0.00016324324324324324,
+      "loss": 0.4373692274093628,
+      "num_input_tokens_seen": 39902,
+      "step": 42,
+      "train_runtime": 197.8938,
+      "train_tokens_per_second": 201.633
+    },
+    {
+      "epoch": 0.010177514792899408,
+      "grad_norm": 0.6083794236183167,
+      "learning_rate": 0.00016216216216216218,
+      "loss": 0.3776765465736389,
+      "num_input_tokens_seen": 40858,
+      "step": 43,
+      "train_runtime": 200.9708,
+      "train_tokens_per_second": 203.303
+    },
+    {
+      "epoch": 0.010414201183431953,
+      "grad_norm": 0.5469992160797119,
+      "learning_rate": 0.0001610810810810811,
+      "loss": 0.31133151054382324,
+      "num_input_tokens_seen": 41760,
+      "step": 44,
+      "train_runtime": 204.1304,
+      "train_tokens_per_second": 204.575
+    },
+    {
+      "epoch": 0.010650887573964497,
+      "grad_norm": 0.6452498435974121,
+      "learning_rate": 0.00016,
+      "loss": 0.42721521854400635,
+      "num_input_tokens_seen": 42740,
+      "step": 45,
+      "train_runtime": 207.1845,
+      "train_tokens_per_second": 206.29
+    },
+    {
+      "epoch": 0.01088757396449704,
+      "grad_norm": 0.5988945960998535,
+      "learning_rate": 0.00015891891891891893,
+      "loss": 0.41375258564949036,
+      "num_input_tokens_seen": 43750,
+      "step": 46,
+      "train_runtime": 210.2912,
+      "train_tokens_per_second": 208.045
+    },
+    {
+      "epoch": 0.011124260355029586,
+      "grad_norm": 0.6452038288116455,
+      "learning_rate": 0.00015783783783783785,
+      "loss": 0.3485276699066162,
+      "num_input_tokens_seen": 44690,
+      "step": 47,
+      "train_runtime": 213.3684,
+      "train_tokens_per_second": 209.45
+    },
+    {
+      "epoch": 0.01136094674556213,
+      "grad_norm": 0.7041454911231995,
+      "learning_rate": 0.00015675675675675676,
+      "loss": 0.3296637535095215,
+      "num_input_tokens_seen": 45666,
+      "step": 48,
+      "train_runtime": 216.4459,
+      "train_tokens_per_second": 210.981
+    },
+    {
+      "epoch": 0.011597633136094675,
+      "grad_norm": 0.6726324558258057,
+      "learning_rate": 0.0001556756756756757,
+      "loss": 0.3179457187652588,
+      "num_input_tokens_seen": 46560,
+      "step": 49,
+      "train_runtime": 219.4697,
+      "train_tokens_per_second": 212.148
+    },
+    {
+      "epoch": 0.011834319526627219,
+      "grad_norm": 0.7513703107833862,
+      "learning_rate": 0.0001545945945945946,
+      "loss": 0.3722391426563263,
+      "num_input_tokens_seen": 47528,
+      "step": 50,
+      "train_runtime": 222.596,
+      "train_tokens_per_second": 213.517
+    },
+    {
+      "epoch": 0.012071005917159764,
+      "grad_norm": 0.6454160213470459,
+      "learning_rate": 0.00015351351351351354,
+      "loss": 0.283376544713974,
+      "num_input_tokens_seen": 48468,
+      "step": 51,
+      "train_runtime": 225.7262,
+      "train_tokens_per_second": 214.72
+    },
+    {
+      "epoch": 0.012307692307692308,
+      "grad_norm": 0.9116244316101074,
+      "learning_rate": 0.00015243243243243243,
+      "loss": 0.4286752939224243,
+      "num_input_tokens_seen": 49444,
+      "step": 52,
+      "train_runtime": 228.803,
+      "train_tokens_per_second": 216.099
+    },
+    {
+      "epoch": 0.012544378698224851,
+      "grad_norm": 0.6157099604606628,
+      "learning_rate": 0.00015135135135135137,
+      "loss": 0.27355721592903137,
+      "num_input_tokens_seen": 50424,
+      "step": 53,
+      "train_runtime": 231.8413,
+      "train_tokens_per_second": 217.494
+    },
+    {
+      "epoch": 0.012781065088757397,
+      "grad_norm": 0.6335808038711548,
+      "learning_rate": 0.00015027027027027028,
+      "loss": 0.37197017669677734,
+      "num_input_tokens_seen": 51328,
+      "step": 54,
+      "train_runtime": 234.9265,
+      "train_tokens_per_second": 218.485
+    },
+    {
+      "epoch": 0.01301775147928994,
+      "grad_norm": 0.6838424205780029,
+      "learning_rate": 0.0001491891891891892,
+      "loss": 0.3504602909088135,
+      "num_input_tokens_seen": 52274,
+      "step": 55,
+      "train_runtime": 238.0114,
+      "train_tokens_per_second": 219.628
+    },
+    {
+      "epoch": 0.013254437869822486,
+      "grad_norm": 0.6566418409347534,
+      "learning_rate": 0.00014810810810810812,
+      "loss": 0.3189927935600281,
+      "num_input_tokens_seen": 53214,
+      "step": 56,
+      "train_runtime": 241.0892,
+      "train_tokens_per_second": 220.723
+    },
+    {
+      "epoch": 0.01349112426035503,
+      "grad_norm": 0.6112971901893616,
+      "learning_rate": 0.00014702702702702703,
+      "loss": 0.3080369830131531,
+      "num_input_tokens_seen": 54162,
+      "step": 57,
+      "train_runtime": 244.2461,
+      "train_tokens_per_second": 221.752
+    },
+    {
+      "epoch": 0.013727810650887575,
+      "grad_norm": 0.6469757556915283,
+      "learning_rate": 0.00014594594594594595,
+      "loss": 0.24279898405075073,
+      "num_input_tokens_seen": 55158,
+      "step": 58,
+      "train_runtime": 247.4064,
+      "train_tokens_per_second": 222.945
+    },
+    {
+      "epoch": 0.013964497041420118,
+      "grad_norm": 0.7099384665489197,
+      "learning_rate": 0.0001448648648648649,
+      "loss": 0.31188705563545227,
+      "num_input_tokens_seen": 56096,
+      "step": 59,
+      "train_runtime": 250.4708,
+      "train_tokens_per_second": 223.962
+    },
+    {
+      "epoch": 0.014201183431952662,
+      "grad_norm": 0.5927040576934814,
+      "learning_rate": 0.00014378378378378378,
+      "loss": 0.25696688890457153,
+      "num_input_tokens_seen": 57012,
+      "step": 60,
+      "train_runtime": 253.7131,
+      "train_tokens_per_second": 224.711
+    },
+    {
+      "epoch": 0.014437869822485207,
+      "grad_norm": 0.5483338236808777,
+      "learning_rate": 0.00014270270270270272,
+      "loss": 0.2725352644920349,
+      "num_input_tokens_seen": 58036,
+      "step": 61,
+      "train_runtime": 260.2844,
+      "train_tokens_per_second": 222.971
+    },
+    {
+      "epoch": 0.014674556213017751,
+      "grad_norm": 0.6806847453117371,
+      "learning_rate": 0.00014162162162162161,
+      "loss": 0.31959983706474304,
+      "num_input_tokens_seen": 59026,
+      "step": 62,
+      "train_runtime": 263.3802,
+      "train_tokens_per_second": 224.109
+    },
+    {
+      "epoch": 0.014911242603550296,
+      "grad_norm": 0.6916660070419312,
+      "learning_rate": 0.00014054054054054056,
+      "loss": 0.312305748462677,
+      "num_input_tokens_seen": 59982,
+      "step": 63,
+      "train_runtime": 266.3794,
+      "train_tokens_per_second": 225.175
+    },
+    {
+      "epoch": 0.01514792899408284,
+      "grad_norm": 0.5516266226768494,
+      "learning_rate": 0.00013945945945945947,
+      "loss": 0.2653953433036804,
+      "num_input_tokens_seen": 60926,
+      "step": 64,
+      "train_runtime": 269.3893,
+      "train_tokens_per_second": 226.163
+    },
+    {
+      "epoch": 0.015384615384615385,
+      "grad_norm": 0.5579270720481873,
+      "learning_rate": 0.0001383783783783784,
+      "loss": 0.20462818443775177,
+      "num_input_tokens_seen": 61844,
+      "step": 65,
+      "train_runtime": 272.3982,
+      "train_tokens_per_second": 227.035
+    },
+    {
+      "epoch": 0.015621301775147929,
+      "grad_norm": 0.7645660638809204,
+      "learning_rate": 0.0001372972972972973,
+      "loss": 0.2650893032550812,
+      "num_input_tokens_seen": 62766,
+      "step": 66,
+      "train_runtime": 275.404,
+      "train_tokens_per_second": 227.905
+    },
+    {
+      "epoch": 0.015857988165680473,
+      "grad_norm": 0.5974738001823425,
+      "learning_rate": 0.00013621621621621622,
+      "loss": 0.21247778832912445,
+      "num_input_tokens_seen": 63690,
+      "step": 67,
+      "train_runtime": 278.4021,
+      "train_tokens_per_second": 228.77
+    },
+    {
+      "epoch": 0.016094674556213016,
+      "grad_norm": 0.5831193327903748,
+      "learning_rate": 0.00013513513513513514,
+      "loss": 0.2024172842502594,
+      "num_input_tokens_seen": 64496,
+      "step": 68,
+      "train_runtime": 281.4313,
+      "train_tokens_per_second": 229.171
+    },
+    {
+      "epoch": 0.016331360946745564,
+      "grad_norm": 0.8678795695304871,
+      "learning_rate": 0.00013405405405405408,
+      "loss": 0.31490638852119446,
+      "num_input_tokens_seen": 65460,
+      "step": 69,
+      "train_runtime": 284.6137,
+      "train_tokens_per_second": 229.996
+    },
+    {
+      "epoch": 0.016568047337278107,
+      "grad_norm": 0.7611344456672668,
+      "learning_rate": 0.00013297297297297297,
+      "loss": 0.24661925435066223,
+      "num_input_tokens_seen": 66374,
+      "step": 70,
+      "train_runtime": 287.7742,
+      "train_tokens_per_second": 230.646
+    },
+    {
+      "epoch": 0.01680473372781065,
+      "grad_norm": 0.6685308814048767,
+      "learning_rate": 0.0001318918918918919,
+      "loss": 0.1843535602092743,
+      "num_input_tokens_seen": 67112,
+      "step": 71,
+      "train_runtime": 290.9321,
+      "train_tokens_per_second": 230.679
+    },
+    {
+      "epoch": 0.017041420118343194,
+      "grad_norm": 0.6150883436203003,
+      "learning_rate": 0.0001308108108108108,
+      "loss": 0.23372295498847961,
+      "num_input_tokens_seen": 68154,
+      "step": 72,
+      "train_runtime": 294.0809,
+      "train_tokens_per_second": 231.753
+    },
+    {
+      "epoch": 0.017278106508875738,
+      "grad_norm": 0.6938812732696533,
+      "learning_rate": 0.00012972972972972974,
+      "loss": 0.22619186341762543,
+      "num_input_tokens_seen": 69102,
+      "step": 73,
+      "train_runtime": 297.1843,
+      "train_tokens_per_second": 232.522
+    },
+    {
+      "epoch": 0.017514792899408285,
+      "grad_norm": 0.617787778377533,
+      "learning_rate": 0.00012864864864864866,
+      "loss": 0.2535328269004822,
+      "num_input_tokens_seen": 70010,
+      "step": 74,
+      "train_runtime": 300.2851,
+      "train_tokens_per_second": 233.145
+    },
+    {
+      "epoch": 0.01775147928994083,
+      "grad_norm": 0.6884900331497192,
+      "learning_rate": 0.00012756756756756758,
+      "loss": 0.21632739901542664,
+      "num_input_tokens_seen": 70940,
+      "step": 75,
+      "train_runtime": 303.3533,
+      "train_tokens_per_second": 233.853
+    },
+    {
+      "epoch": 0.017988165680473372,
+      "grad_norm": 0.5782189965248108,
+      "learning_rate": 0.0001264864864864865,
+      "loss": 0.20167675614356995,
+      "num_input_tokens_seen": 71862,
+      "step": 76,
+      "train_runtime": 306.4503,
+      "train_tokens_per_second": 234.498
+    },
+    {
+      "epoch": 0.018224852071005916,
+      "grad_norm": 0.6541483402252197,
+      "learning_rate": 0.0001254054054054054,
+      "loss": 0.23231221735477448,
+      "num_input_tokens_seen": 72812,
+      "step": 77,
+      "train_runtime": 309.5743,
+      "train_tokens_per_second": 235.2
+    },
+    {
+      "epoch": 0.018461538461538463,
+      "grad_norm": 0.7524886727333069,
+      "learning_rate": 0.00012432432432432433,
+      "loss": 0.27632662653923035,
+      "num_input_tokens_seen": 73774,
+      "step": 78,
+      "train_runtime": 312.6963,
+      "train_tokens_per_second": 235.929
+    },
+    {
+      "epoch": 0.018698224852071007,
+      "grad_norm": 0.716282308101654,
+      "learning_rate": 0.00012324324324324327,
+      "loss": 0.2734939754009247,
+      "num_input_tokens_seen": 74716,
+      "step": 79,
+      "train_runtime": 315.7612,
+      "train_tokens_per_second": 236.622
+    },
+    {
+      "epoch": 0.01893491124260355,
+      "grad_norm": 0.7010631561279297,
+      "learning_rate": 0.00012216216216216216,
+      "loss": 0.2774362564086914,
+      "num_input_tokens_seen": 75692,
+      "step": 80,
+      "train_runtime": 318.7983,
+      "train_tokens_per_second": 237.429
+    },
+    {
+      "epoch": 0.019171597633136094,
+      "grad_norm": 0.6561240553855896,
+      "learning_rate": 0.00012108108108108109,
+      "loss": 0.21640686690807343,
+      "num_input_tokens_seen": 76558,
+      "step": 81,
+      "train_runtime": 321.889,
+      "train_tokens_per_second": 237.84
+    },
+    {
+      "epoch": 0.019408284023668638,
+      "grad_norm": 0.5552831888198853,
+      "learning_rate": 0.00012,
+      "loss": 0.21232956647872925,
+      "num_input_tokens_seen": 77408,
+      "step": 82,
+      "train_runtime": 325.0469,
+      "train_tokens_per_second": 238.144
+    },
+    {
+      "epoch": 0.019644970414201185,
+      "grad_norm": 0.5905120372772217,
+      "learning_rate": 0.00011891891891891893,
+      "loss": 0.22443550825119019,
+      "num_input_tokens_seen": 78278,
+      "step": 83,
+      "train_runtime": 328.099,
+      "train_tokens_per_second": 238.58
+    },
+    {
+      "epoch": 0.01988165680473373,
+      "grad_norm": 0.6606366634368896,
+      "learning_rate": 0.00011783783783783784,
+      "loss": 0.2400747388601303,
+      "num_input_tokens_seen": 79262,
+      "step": 84,
+      "train_runtime": 331.1361,
+      "train_tokens_per_second": 239.364
+    },
+    {
+      "epoch": 0.020118343195266272,
+      "grad_norm": 0.6508055329322815,
+      "learning_rate": 0.00011675675675675676,
+      "loss": 0.19072499871253967,
+      "num_input_tokens_seen": 80144,
+      "step": 85,
+      "train_runtime": 334.2158,
+      "train_tokens_per_second": 239.797
+    },
+    {
+      "epoch": 0.020355029585798816,
+      "grad_norm": 0.606562614440918,
+      "learning_rate": 0.00011567567567567568,
+      "loss": 0.20951862633228302,
+      "num_input_tokens_seen": 81108,
+      "step": 86,
+      "train_runtime": 337.3105,
+      "train_tokens_per_second": 240.455
+    },
+    {
+      "epoch": 0.02059171597633136,
+      "grad_norm": 0.6757521629333496,
+      "learning_rate": 0.00011459459459459461,
+      "loss": 0.17614495754241943,
+      "num_input_tokens_seen": 82032,
+      "step": 87,
+      "train_runtime": 340.3438,
+      "train_tokens_per_second": 241.027
+    },
+    {
+      "epoch": 0.020828402366863907,
+      "grad_norm": 0.671481728553772,
+      "learning_rate": 0.00011351351351351351,
+      "loss": 0.1901710331439972,
+      "num_input_tokens_seen": 82954,
+      "step": 88,
+      "train_runtime": 343.4059,
+      "train_tokens_per_second": 241.563
+    },
+    {
+      "epoch": 0.02106508875739645,
+      "grad_norm": 0.5919027924537659,
+      "learning_rate": 0.00011243243243243244,
+      "loss": 0.1563737988471985,
+      "num_input_tokens_seen": 83880,
+      "step": 89,
+      "train_runtime": 346.5125,
+      "train_tokens_per_second": 242.069
+    },
+    {
+      "epoch": 0.021301775147928994,
+      "grad_norm": 0.7108309268951416,
+      "learning_rate": 0.00011135135135135135,
+      "loss": 0.17256894707679749,
+      "num_input_tokens_seen": 84852,
+      "step": 90,
+      "train_runtime": 349.6508,
+      "train_tokens_per_second": 242.676
+    },
+    {
+      "epoch": 0.021538461538461538,
+      "grad_norm": 0.8608420491218567,
+      "learning_rate": 0.00011027027027027029,
+      "loss": 0.1845530867576599,
+      "num_input_tokens_seen": 85820,
+      "step": 91,
+      "train_runtime": 356.267,
+      "train_tokens_per_second": 240.887
+    },
+    {
+      "epoch": 0.02177514792899408,
+      "grad_norm": 0.9677010774612427,
+      "learning_rate": 0.00010918918918918919,
+      "loss": 0.24358105659484863,
+      "num_input_tokens_seen": 86770,
+      "step": 92,
+      "train_runtime": 359.3722,
+      "train_tokens_per_second": 241.449
+    },
+    {
+      "epoch": 0.02201183431952663,
+      "grad_norm": 0.6302966475486755,
+      "learning_rate": 0.00010810810810810812,
+      "loss": 0.18155133724212646,
+      "num_input_tokens_seen": 87736,
+      "step": 93,
+      "train_runtime": 362.5874,
+      "train_tokens_per_second": 241.972
+    },
+    {
+      "epoch": 0.022248520710059172,
+      "grad_norm": 0.7171812653541565,
+      "learning_rate": 0.00010702702702702702,
+      "loss": 0.15349116921424866,
+      "num_input_tokens_seen": 88626,
+      "step": 94,
+      "train_runtime": 365.7055,
+      "train_tokens_per_second": 242.343
+    },
+    {
+      "epoch": 0.022485207100591716,
+      "grad_norm": 0.7326887845993042,
+      "learning_rate": 0.00010594594594594595,
+      "loss": 0.18243758380413055,
+      "num_input_tokens_seen": 89548,
+      "step": 95,
+      "train_runtime": 368.799,
+      "train_tokens_per_second": 242.81
+    },
+    {
+      "epoch": 0.02272189349112426,
+      "grad_norm": 0.6686019897460938,
+      "learning_rate": 0.00010486486486486487,
+      "loss": 0.15622465312480927,
+      "num_input_tokens_seen": 90504,
+      "step": 96,
+      "train_runtime": 371.8404,
+      "train_tokens_per_second": 243.395
+    },
+    {
+      "epoch": 0.022958579881656806,
+      "grad_norm": 0.6306503415107727,
+      "learning_rate": 0.0001037837837837838,
+      "loss": 0.1272117793560028,
+      "num_input_tokens_seen": 91454,
+      "step": 97,
+      "train_runtime": 375.0199,
+      "train_tokens_per_second": 243.864
+    },
+    {
+      "epoch": 0.02319526627218935,
+      "grad_norm": 0.6068493127822876,
+      "learning_rate": 0.0001027027027027027,
+      "loss": 0.1577155441045761,
+      "num_input_tokens_seen": 92466,
+      "step": 98,
+      "train_runtime": 378.0978,
+      "train_tokens_per_second": 244.556
+    },
+    {
+      "epoch": 0.023431952662721894,
+      "grad_norm": 0.7263635993003845,
+      "learning_rate": 0.00010162162162162163,
+      "loss": 0.1845340132713318,
+      "num_input_tokens_seen": 93398,
+      "step": 99,
+      "train_runtime": 381.1358,
+      "train_tokens_per_second": 245.052
+    },
+    {
+      "epoch": 0.023668639053254437,
+      "grad_norm": 0.6466794013977051,
+      "learning_rate": 0.00010054054054054053,
+      "loss": 0.14443959295749664,
+      "num_input_tokens_seen": 94230,
+      "step": 100,
+      "train_runtime": 384.2906,
+      "train_tokens_per_second": 245.205
+    },
+    {
+      "epoch": 0.02390532544378698,
+      "grad_norm": 0.6924043297767639,
+      "learning_rate": 9.945945945945948e-05,
+      "loss": 0.18473166227340698,
+      "num_input_tokens_seen": 95132,
+      "step": 101,
+      "train_runtime": 387.5005,
+      "train_tokens_per_second": 245.502
+    },
+    {
+      "epoch": 0.024142011834319528,
+      "grad_norm": 0.732337236404419,
+      "learning_rate": 9.837837837837839e-05,
+      "loss": 0.16353662312030792,
+      "num_input_tokens_seen": 96080,
+      "step": 102,
+      "train_runtime": 390.584,
+      "train_tokens_per_second": 245.991
+    },
+    {
+      "epoch": 0.02437869822485207,
+      "grad_norm": 0.5956932902336121,
+      "learning_rate": 9.729729729729731e-05,
+      "loss": 0.16359847784042358,
+      "num_input_tokens_seen": 97048,
+      "step": 103,
+      "train_runtime": 393.6474,
+      "train_tokens_per_second": 246.535
+    },
+    {
+      "epoch": 0.024615384615384615,
+      "grad_norm": 0.6137388348579407,
+      "learning_rate": 9.621621621621622e-05,
+      "loss": 0.15779417753219604,
+      "num_input_tokens_seen": 97986,
+      "step": 104,
+      "train_runtime": 396.7042,
+      "train_tokens_per_second": 247.0
+    },
+    {
+      "epoch": 0.02485207100591716,
+      "grad_norm": 0.7936599254608154,
+      "learning_rate": 9.513513513513514e-05,
+      "loss": 0.21357379853725433,
+      "num_input_tokens_seen": 98894,
+      "step": 105,
+      "train_runtime": 399.8228,
+      "train_tokens_per_second": 247.345
+    },
+    {
+      "epoch": 0.025088757396449703,
+      "grad_norm": 0.6574507355690002,
+      "learning_rate": 9.405405405405407e-05,
+      "loss": 0.1685573309659958,
+      "num_input_tokens_seen": 99856,
+      "step": 106,
+      "train_runtime": 402.8867,
+      "train_tokens_per_second": 247.851
+    },
+    {
+      "epoch": 0.02532544378698225,
+      "grad_norm": 0.5891634821891785,
+      "learning_rate": 9.297297297297299e-05,
+      "loss": 0.12082140147686005,
+      "num_input_tokens_seen": 100810,
+      "step": 107,
+      "train_runtime": 405.9752,
+      "train_tokens_per_second": 248.316
+    },
+    {
+      "epoch": 0.025562130177514793,
+      "grad_norm": 0.6624342799186707,
+      "learning_rate": 9.18918918918919e-05,
+      "loss": 0.1473795771598816,
+      "num_input_tokens_seen": 101744,
+      "step": 108,
+      "train_runtime": 409.0084,
+      "train_tokens_per_second": 248.758
+    },
+    {
+      "epoch": 0.025798816568047337,
+      "grad_norm": 0.5968036651611328,
+      "learning_rate": 9.081081081081082e-05,
+      "loss": 0.12923751771450043,
+      "num_input_tokens_seen": 102702,
+      "step": 109,
+      "train_runtime": 412.199,
+      "train_tokens_per_second": 249.156
+    },
+    {
+      "epoch": 0.02603550295857988,
+      "grad_norm": 0.5954580307006836,
+      "learning_rate": 8.972972972972973e-05,
+      "loss": 0.1161399856209755,
+      "num_input_tokens_seen": 103672,
+      "step": 110,
+      "train_runtime": 415.3736,
+      "train_tokens_per_second": 249.587
+    },
+    {
+      "epoch": 0.026272189349112424,
+      "grad_norm": 0.6139379739761353,
+      "learning_rate": 8.864864864864866e-05,
+      "loss": 0.12352899461984634,
+      "num_input_tokens_seen": 104598,
+      "step": 111,
+      "train_runtime": 418.3271,
+      "train_tokens_per_second": 250.039
+    },
+    {
+      "epoch": 0.02650887573964497,
+      "grad_norm": 0.7933095097541809,
+      "learning_rate": 8.756756756756758e-05,
+      "loss": 0.1709994524717331,
+      "num_input_tokens_seen": 105580,
+      "step": 112,
+      "train_runtime": 421.3565,
+      "train_tokens_per_second": 250.572
+    },
+    {
+      "epoch": 0.026745562130177515,
+      "grad_norm": 0.7641370892524719,
+      "learning_rate": 8.64864864864865e-05,
+      "loss": 0.13086311519145966,
+      "num_input_tokens_seen": 106444,
+      "step": 113,
+      "train_runtime": 424.4668,
+      "train_tokens_per_second": 250.771
+    },
+    {
+      "epoch": 0.02698224852071006,
+      "grad_norm": 0.7611938118934631,
+      "learning_rate": 8.540540540540541e-05,
+      "loss": 0.16537640988826752,
+      "num_input_tokens_seen": 107454,
+      "step": 114,
+      "train_runtime": 427.5,
+      "train_tokens_per_second": 251.354
+    },
+    {
+      "epoch": 0.027218934911242602,
+      "grad_norm": 0.7495304346084595,
+      "learning_rate": 8.432432432432433e-05,
+      "loss": 0.14228317141532898,
+      "num_input_tokens_seen": 108426,
+      "step": 115,
+      "train_runtime": 430.5035,
+      "train_tokens_per_second": 251.859
+    },
+    {
+      "epoch": 0.02745562130177515,
+      "grad_norm": 1.2078282833099365,
+      "learning_rate": 8.324324324324326e-05,
+      "loss": 0.10530930012464523,
+      "num_input_tokens_seen": 109446,
+      "step": 116,
+      "train_runtime": 433.4964,
+      "train_tokens_per_second": 252.473
+    },
+    {
+      "epoch": 0.027692307692307693,
+      "grad_norm": 0.6765572428703308,
+      "learning_rate": 8.216216216216217e-05,
+      "loss": 0.10717278718948364,
+      "num_input_tokens_seen": 110374,
+      "step": 117,
+      "train_runtime": 436.5901,
+      "train_tokens_per_second": 252.809
+    },
+    {
+      "epoch": 0.027928994082840237,
+      "grad_norm": 0.8501551151275635,
+      "learning_rate": 8.108108108108109e-05,
+      "loss": 0.17784273624420166,
+      "num_input_tokens_seen": 111340,
+      "step": 118,
+      "train_runtime": 439.6526,
+      "train_tokens_per_second": 253.245
+    },
+    {
+      "epoch": 0.02816568047337278,
+      "grad_norm": 0.7583926320075989,
+      "learning_rate": 8e-05,
+      "loss": 0.16588062047958374,
+      "num_input_tokens_seen": 112288,
+      "step": 119,
+      "train_runtime": 442.8046,
+      "train_tokens_per_second": 253.584
+    },
+    {
+      "epoch": 0.028402366863905324,
+      "grad_norm": 0.6620173454284668,
+      "learning_rate": 7.891891891891892e-05,
+      "loss": 0.11676295101642609,
+      "num_input_tokens_seen": 113206,
+      "step": 120,
+      "train_runtime": 445.9682,
+      "train_tokens_per_second": 253.843
+    },
+    {
+      "epoch": 0.02863905325443787,
+      "grad_norm": 0.6844660639762878,
+      "learning_rate": 7.783783783783785e-05,
+      "loss": 0.09329869598150253,
+      "num_input_tokens_seen": 114134,
+      "step": 121,
+      "train_runtime": 452.5692,
+      "train_tokens_per_second": 252.191
+    },
+    {
+      "epoch": 0.028875739644970415,
+      "grad_norm": 0.7968376874923706,
+      "learning_rate": 7.675675675675677e-05,
+      "loss": 0.13320565223693848,
+      "num_input_tokens_seen": 115088,
+      "step": 122,
+      "train_runtime": 455.6245,
+      "train_tokens_per_second": 252.594
+    },
+    {
+      "epoch": 0.02911242603550296,
+      "grad_norm": 0.8079301118850708,
+      "learning_rate": 7.567567567567568e-05,
+      "loss": 0.1387016326189041,
+      "num_input_tokens_seen": 116006,
+      "step": 123,
+      "train_runtime": 458.7601,
+      "train_tokens_per_second": 252.869
+    },
+    {
+      "epoch": 0.029349112426035502,
+      "grad_norm": 1.1301748752593994,
+      "learning_rate": 7.45945945945946e-05,
+      "loss": 0.197790265083313,
+      "num_input_tokens_seen": 116958,
+      "step": 124,
+      "train_runtime": 461.861,
+      "train_tokens_per_second": 253.232
+    },
+    {
+      "epoch": 0.029585798816568046,
+      "grad_norm": 0.7272042632102966,
+      "learning_rate": 7.351351351351352e-05,
+      "loss": 0.12121891975402832,
+      "num_input_tokens_seen": 117886,
+      "step": 125,
+      "train_runtime": 465.0328,
+      "train_tokens_per_second": 253.5
+    },
+    {
+      "epoch": 0.029822485207100593,
+      "grad_norm": 0.6021063923835754,
+      "learning_rate": 7.243243243243245e-05,
+      "loss": 0.08234579861164093,
+      "num_input_tokens_seen": 118806,
+      "step": 126,
+      "train_runtime": 468.1518,
+      "train_tokens_per_second": 253.777
+    },
+    {
+      "epoch": 0.030059171597633137,
+      "grad_norm": 0.5659137964248657,
+      "learning_rate": 7.135135135135136e-05,
+      "loss": 0.07469362020492554,
+      "num_input_tokens_seen": 119716,
+      "step": 127,
+      "train_runtime": 471.2559,
+      "train_tokens_per_second": 254.036
+    },
+    {
+      "epoch": 0.03029585798816568,
+      "grad_norm": 0.7604466080665588,
+      "learning_rate": 7.027027027027028e-05,
+      "loss": 0.15167035162448883,
+      "num_input_tokens_seen": 120710,
+      "step": 128,
+      "train_runtime": 474.3536,
+      "train_tokens_per_second": 254.473
+    },
+    {
+      "epoch": 0.030532544378698224,
+      "grad_norm": 0.898281455039978,
+      "learning_rate": 6.91891891891892e-05,
+      "loss": 0.18358615040779114,
+      "num_input_tokens_seen": 121668,
+      "step": 129,
+      "train_runtime": 477.4676,
+      "train_tokens_per_second": 254.819
+    },
+    {
+      "epoch": 0.03076923076923077,
+      "grad_norm": 1.046539545059204,
+      "learning_rate": 6.810810810810811e-05,
+      "loss": 0.14173445105552673,
+      "num_input_tokens_seen": 122654,
+      "step": 130,
+      "train_runtime": 480.6242,
+      "train_tokens_per_second": 255.197
+    },
+    {
+      "epoch": 0.031005917159763315,
+      "grad_norm": 0.689860463142395,
+      "learning_rate": 6.702702702702704e-05,
+      "loss": 0.1232977956533432,
+      "num_input_tokens_seen": 123610,
+      "step": 131,
+      "train_runtime": 483.7904,
+      "train_tokens_per_second": 255.503
+    },
+    {
+      "epoch": 0.031242603550295858,
+      "grad_norm": 0.6417210698127747,
+      "learning_rate": 6.594594594594596e-05,
+      "loss": 0.08111131936311722,
+      "num_input_tokens_seen": 124526,
+      "step": 132,
+      "train_runtime": 486.9241,
+      "train_tokens_per_second": 255.74
+    },
+    {
+      "epoch": 0.0314792899408284,
+      "grad_norm": 0.8019670844078064,
+      "learning_rate": 6.486486486486487e-05,
+      "loss": 0.13235916197299957,
+      "num_input_tokens_seen": 125438,
+      "step": 133,
+      "train_runtime": 490.0416,
+      "train_tokens_per_second": 255.974
+    },
+    {
+      "epoch": 0.031715976331360946,
+      "grad_norm": 0.8618372082710266,
+      "learning_rate": 6.378378378378379e-05,
+      "loss": 0.11209192872047424,
+      "num_input_tokens_seen": 126378,
+      "step": 134,
+      "train_runtime": 493.0816,
+      "train_tokens_per_second": 256.302
+    },
+    {
+      "epoch": 0.03195266272189349,
+      "grad_norm": 0.6566123962402344,
+      "learning_rate": 6.27027027027027e-05,
+      "loss": 0.08107412606477737,
+      "num_input_tokens_seen": 127280,
+      "step": 135,
+      "train_runtime": 496.1373,
+      "train_tokens_per_second": 256.542
+    },
+    {
+      "epoch": 0.03218934911242603,
+      "grad_norm": 0.671886682510376,
+      "learning_rate": 6.162162162162163e-05,
+      "loss": 0.10395485162734985,
+      "num_input_tokens_seen": 128246,
+      "step": 136,
+      "train_runtime": 499.2198,
+      "train_tokens_per_second": 256.893
+    },
+    {
+      "epoch": 0.032426035502958576,
+      "grad_norm": 0.5853029489517212,
+      "learning_rate": 6.0540540540540543e-05,
+      "loss": 0.06830425560474396,
+      "num_input_tokens_seen": 129142,
+      "step": 137,
+      "train_runtime": 502.2719,
+      "train_tokens_per_second": 257.116
+    },
+    {
+      "epoch": 0.03266272189349113,
+      "grad_norm": 0.9871621131896973,
+      "learning_rate": 5.9459459459459466e-05,
+      "loss": 0.14138084650039673,
+      "num_input_tokens_seen": 130060,
+      "step": 138,
+      "train_runtime": 505.3687,
+      "train_tokens_per_second": 257.357
+    },
+    {
+      "epoch": 0.03289940828402367,
+      "grad_norm": 0.6716732978820801,
+      "learning_rate": 5.837837837837838e-05,
+      "loss": 0.07525799423456192,
+      "num_input_tokens_seen": 130982,
+      "step": 139,
+      "train_runtime": 508.4248,
+      "train_tokens_per_second": 257.623
+    },
+    {
+      "epoch": 0.033136094674556214,
+      "grad_norm": 0.7177789807319641,
+      "learning_rate": 5.7297297297297305e-05,
+      "loss": 0.09517940878868103,
+      "num_input_tokens_seen": 131900,
+      "step": 140,
+      "train_runtime": 511.57,
+      "train_tokens_per_second": 257.834
+    },
+    {
+      "epoch": 0.03337278106508876,
+      "grad_norm": 0.703551709651947,
+      "learning_rate": 5.621621621621622e-05,
+      "loss": 0.09361469000577927,
+      "num_input_tokens_seen": 132890,
+      "step": 141,
+      "train_runtime": 514.7186,
+      "train_tokens_per_second": 258.18
+    },
+    {
+      "epoch": 0.0336094674556213,
+      "grad_norm": 0.7156357765197754,
+      "learning_rate": 5.5135135135135144e-05,
+      "loss": 0.08832181245088577,
+      "num_input_tokens_seen": 133810,
+      "step": 142,
+      "train_runtime": 517.7644,
+      "train_tokens_per_second": 258.438
+    },
+    {
+      "epoch": 0.033846153846153845,
+      "grad_norm": 0.7757886648178101,
+      "learning_rate": 5.405405405405406e-05,
+      "loss": 0.12478049844503403,
+      "num_input_tokens_seen": 134758,
+      "step": 143,
+      "train_runtime": 520.8215,
+      "train_tokens_per_second": 258.741
+    },
+    {
+      "epoch": 0.03408284023668639,
+      "grad_norm": 0.6047410368919373,
+      "learning_rate": 5.2972972972972976e-05,
+      "loss": 0.07645335048437119,
+      "num_input_tokens_seen": 135724,
+      "step": 144,
+      "train_runtime": 523.9787,
+      "train_tokens_per_second": 259.026
+    },
+    {
+      "epoch": 0.03431952662721893,
+      "grad_norm": 0.7750188708305359,
+      "learning_rate": 5.18918918918919e-05,
+      "loss": 0.10904290527105331,
+      "num_input_tokens_seen": 136662,
+      "step": 145,
+      "train_runtime": 527.0633,
+      "train_tokens_per_second": 259.29
+    },
+    {
+      "epoch": 0.034556213017751476,
+      "grad_norm": 0.6400149464607239,
+      "learning_rate": 5.0810810810810815e-05,
+      "loss": 0.07525563985109329,
+      "num_input_tokens_seen": 137628,
+      "step": 146,
+      "train_runtime": 530.1299,
+      "train_tokens_per_second": 259.612
+    },
+    {
+      "epoch": 0.03479289940828403,
+      "grad_norm": 0.6681646108627319,
+      "learning_rate": 4.972972972972974e-05,
+      "loss": 0.08536849915981293,
+      "num_input_tokens_seen": 138610,
+      "step": 147,
+      "train_runtime": 533.159,
+      "train_tokens_per_second": 259.979
+    },
+    {
+      "epoch": 0.03502958579881657,
+      "grad_norm": 0.6158885359764099,
+      "learning_rate": 4.8648648648648654e-05,
+      "loss": 0.0753958523273468,
+      "num_input_tokens_seen": 139486,
+      "step": 148,
+      "train_runtime": 536.2632,
+      "train_tokens_per_second": 260.107
+    },
+    {
+      "epoch": 0.035266272189349114,
+      "grad_norm": 0.665565550327301,
+      "learning_rate": 4.756756756756757e-05,
+      "loss": 0.08198000490665436,
+      "num_input_tokens_seen": 140440,
+      "step": 149,
+      "train_runtime": 539.3165,
+      "train_tokens_per_second": 260.404
+    },
+    {
+      "epoch": 0.03550295857988166,
+      "grad_norm": 0.6818353533744812,
+      "learning_rate": 4.648648648648649e-05,
+      "loss": 0.0710655227303505,
+      "num_input_tokens_seen": 141344,
+      "step": 150,
+      "train_runtime": 542.3824,
+      "train_tokens_per_second": 260.598
+    },
+    {
+      "epoch": 0.0357396449704142,
+      "grad_norm": 0.5292275547981262,
+      "learning_rate": 4.540540540540541e-05,
+      "loss": 0.04743894189596176,
+      "num_input_tokens_seen": 142242,
+      "step": 151,
+      "train_runtime": 549.1326,
+      "train_tokens_per_second": 259.03
+    },
+    {
+      "epoch": 0.035976331360946745,
+      "grad_norm": 0.9436084032058716,
+      "learning_rate": 4.432432432432433e-05,
+      "loss": 0.10009428858757019,
+      "num_input_tokens_seen": 143104,
+      "step": 152,
+      "train_runtime": 552.245,
+      "train_tokens_per_second": 259.131
+    },
+    {
+      "epoch": 0.03621301775147929,
+      "grad_norm": 0.8146379590034485,
+      "learning_rate": 4.324324324324325e-05,
+      "loss": 0.08397847414016724,
+      "num_input_tokens_seen": 144036,
+      "step": 153,
+      "train_runtime": 555.3194,
+      "train_tokens_per_second": 259.375
+    },
+    {
+      "epoch": 0.03644970414201183,
+      "grad_norm": 0.6370963454246521,
+      "learning_rate": 4.2162162162162164e-05,
+      "loss": 0.0647936463356018,
+      "num_input_tokens_seen": 144978,
+      "step": 154,
+      "train_runtime": 558.5158,
+      "train_tokens_per_second": 259.577
+    },
+    {
+      "epoch": 0.036686390532544376,
+      "grad_norm": 0.7876921892166138,
+      "learning_rate": 4.108108108108109e-05,
+      "loss": 0.10044769942760468,
+      "num_input_tokens_seen": 145932,
+      "step": 155,
+      "train_runtime": 561.6626,
+      "train_tokens_per_second": 259.821
+    },
+    {
+      "epoch": 0.036923076923076927,
+      "grad_norm": 0.5711075067520142,
+      "learning_rate": 4e-05,
+      "loss": 0.0628824308514595,
+      "num_input_tokens_seen": 146822,
+      "step": 156,
+      "train_runtime": 564.7686,
+      "train_tokens_per_second": 259.968
+    },
+    {
+      "epoch": 0.03715976331360947,
+      "grad_norm": 0.6890460848808289,
+      "learning_rate": 3.8918918918918926e-05,
+      "loss": 0.0714673101902008,
+      "num_input_tokens_seen": 147746,
+      "step": 157,
+      "train_runtime": 567.7959,
+      "train_tokens_per_second": 260.21
+    },
+    {
+      "epoch": 0.037396449704142014,
+      "grad_norm": 0.6936295032501221,
+      "learning_rate": 3.783783783783784e-05,
+      "loss": 0.05670904368162155,
+      "num_input_tokens_seen": 148648,
+      "step": 158,
+      "train_runtime": 570.8255,
+      "train_tokens_per_second": 260.409
+    },
+    {
+      "epoch": 0.03763313609467456,
+      "grad_norm": 0.6268077492713928,
+      "learning_rate": 3.675675675675676e-05,
+      "loss": 0.04924366623163223,
+      "num_input_tokens_seen": 149622,
+      "step": 159,
+      "train_runtime": 573.9724,
+      "train_tokens_per_second": 260.678
+    },
+    {
+      "epoch": 0.0378698224852071,
+      "grad_norm": 0.7037569284439087,
+      "learning_rate": 3.567567567567568e-05,
+      "loss": 0.06151504069566727,
+      "num_input_tokens_seen": 150586,
+      "step": 160,
+      "train_runtime": 577.103,
+      "train_tokens_per_second": 260.934
+    },
+    {
+      "epoch": 0.038106508875739645,
+      "grad_norm": 0.6471953392028809,
+      "learning_rate": 3.45945945945946e-05,
+      "loss": 0.040921665728092194,
+      "num_input_tokens_seen": 151442,
+      "step": 161,
+      "train_runtime": 580.1219,
+      "train_tokens_per_second": 261.052
+    },
+    {
+      "epoch": 0.03834319526627219,
+      "grad_norm": 0.7046090960502625,
+      "learning_rate": 3.351351351351352e-05,
+      "loss": 0.05204992741346359,
+      "num_input_tokens_seen": 152350,
+      "step": 162,
+      "train_runtime": 583.1537,
+      "train_tokens_per_second": 261.252
+    },
+    {
+      "epoch": 0.03857988165680473,
+      "grad_norm": 1.0495421886444092,
+      "learning_rate": 3.2432432432432436e-05,
+      "loss": 0.1057022288441658,
+      "num_input_tokens_seen": 153278,
+      "step": 163,
+      "train_runtime": 586.3134,
+      "train_tokens_per_second": 261.427
+    },
+    {
+      "epoch": 0.038816568047337276,
+      "grad_norm": 0.6432052850723267,
+      "learning_rate": 3.135135135135135e-05,
+      "loss": 0.05509451404213905,
+      "num_input_tokens_seen": 154178,
+      "step": 164,
+      "train_runtime": 589.3544,
+      "train_tokens_per_second": 261.605
+    },
+    {
+      "epoch": 0.03905325443786982,
+      "grad_norm": 0.6547747254371643,
+      "learning_rate": 3.0270270270270272e-05,
+      "loss": 0.04602127522230148,
+      "num_input_tokens_seen": 155080,
+      "step": 165,
+      "train_runtime": 592.3642,
+      "train_tokens_per_second": 261.798
+    },
+    {
+      "epoch": 0.03928994082840237,
+      "grad_norm": 0.6700029969215393,
+      "learning_rate": 2.918918918918919e-05,
+      "loss": 0.05721529945731163,
+      "num_input_tokens_seen": 156140,
+      "step": 166,
+      "train_runtime": 595.4897,
+      "train_tokens_per_second": 262.204
+    },
+    {
+      "epoch": 0.039526627218934914,
+      "grad_norm": 0.9145491719245911,
+      "learning_rate": 2.810810810810811e-05,
+      "loss": 0.06747015565633774,
+      "num_input_tokens_seen": 157106,
+      "step": 167,
+      "train_runtime": 598.5891,
+      "train_tokens_per_second": 262.461
+    },
+    {
+      "epoch": 0.03976331360946746,
+      "grad_norm": 0.8798087239265442,
+      "learning_rate": 2.702702702702703e-05,
+      "loss": 0.08232270181179047,
+      "num_input_tokens_seen": 158056,
+      "step": 168,
+      "train_runtime": 601.7315,
+      "train_tokens_per_second": 262.669
+    },
+    {
+      "epoch": 0.04,
+      "grad_norm": 1.0618623495101929,
+      "learning_rate": 2.594594594594595e-05,
+      "loss": 0.09569647908210754,
+      "num_input_tokens_seen": 159060,
+      "step": 169,
+      "train_runtime": 604.8838,
+      "train_tokens_per_second": 262.96
+    },
+    {
+      "epoch": 0.040236686390532544,
+      "grad_norm": 0.6945156455039978,
+      "learning_rate": 2.486486486486487e-05,
+      "loss": 0.0597086027264595,
+      "num_input_tokens_seen": 160054,
+      "step": 170,
+      "train_runtime": 608.004,
+      "train_tokens_per_second": 263.245
+    },
+    {
+      "epoch": 0.04047337278106509,
+      "grad_norm": 0.6867018342018127,
+      "learning_rate": 2.3783783783783785e-05,
+      "loss": 0.053483735769987106,
+      "num_input_tokens_seen": 160992,
+      "step": 171,
+      "train_runtime": 611.0992,
+      "train_tokens_per_second": 263.447
+    },
+    {
+      "epoch": 0.04071005917159763,
+      "grad_norm": 0.9504451751708984,
+      "learning_rate": 2.2702702702702705e-05,
+      "loss": 0.07532191276550293,
+      "num_input_tokens_seen": 161910,
+      "step": 172,
+      "train_runtime": 614.2523,
+      "train_tokens_per_second": 263.589
+    },
+    {
+      "epoch": 0.040946745562130175,
+      "grad_norm": 0.6639146208763123,
+      "learning_rate": 2.1621621621621624e-05,
+      "loss": 0.04415765404701233,
+      "num_input_tokens_seen": 162810,
+      "step": 173,
+      "train_runtime": 617.2712,
+      "train_tokens_per_second": 263.758
+    },
+    {
+      "epoch": 0.04118343195266272,
+      "grad_norm": 0.5948973894119263,
+      "learning_rate": 2.0540540540540544e-05,
+      "loss": 0.04589955136179924,
+      "num_input_tokens_seen": 163792,
+      "step": 174,
+      "train_runtime": 620.3367,
+      "train_tokens_per_second": 264.037
+    },
+    {
+      "epoch": 0.04142011834319527,
+      "grad_norm": 0.8319454193115234,
+      "learning_rate": 1.9459459459459463e-05,
+      "loss": 0.07309269905090332,
+      "num_input_tokens_seen": 164770,
+      "step": 175,
+      "train_runtime": 623.4097,
+      "train_tokens_per_second": 264.305
+    },
+    {
+      "epoch": 0.04165680473372781,
+      "grad_norm": 0.591090202331543,
+      "learning_rate": 1.837837837837838e-05,
+      "loss": 0.04063474386930466,
+      "num_input_tokens_seen": 165708,
+      "step": 176,
+      "train_runtime": 626.513,
+      "train_tokens_per_second": 264.493
+    },
+    {
+      "epoch": 0.04189349112426036,
+      "grad_norm": 0.5455971360206604,
+      "learning_rate": 1.72972972972973e-05,
+      "loss": 0.0511426106095314,
+      "num_input_tokens_seen": 166654,
+      "step": 177,
+      "train_runtime": 629.5606,
+      "train_tokens_per_second": 264.715
+    },
+    {
+      "epoch": 0.0421301775147929,
+      "grad_norm": 0.7040805816650391,
+      "learning_rate": 1.6216216216216218e-05,
+      "loss": 0.06684890389442444,
+      "num_input_tokens_seen": 167586,
+      "step": 178,
+      "train_runtime": 632.5911,
+      "train_tokens_per_second": 264.92
+    },
+    {
+      "epoch": 0.042366863905325444,
+      "grad_norm": 0.9840870499610901,
+      "learning_rate": 1.5135135135135136e-05,
+      "loss": 0.08544427156448364,
+      "num_input_tokens_seen": 168558,
+      "step": 179,
+      "train_runtime": 635.6343,
+      "train_tokens_per_second": 265.181
+    },
+    {
+      "epoch": 0.04260355029585799,
+      "grad_norm": 0.763282835483551,
+      "learning_rate": 1.4054054054054055e-05,
+      "loss": 0.05402141064405441,
+      "num_input_tokens_seen": 169594,
+      "step": 180,
+      "train_runtime": 638.8133,
+      "train_tokens_per_second": 265.483
+    }
+  ],
+  "logging_steps": 1,
+  "max_steps": 190,
+  "num_input_tokens_seen": 169594,
+  "num_train_epochs": 1,
+  "save_steps": 30,
+  "stateful_callbacks": {
+    "TrainerControl": {
+      "args": {
+        "should_epoch_stop": false,
+        "should_evaluate": false,
+        "should_log": false,
+        "should_save": true,
+        "should_training_stop": false
+      },
+      "attributes": {}
+    }
+  },
+  "total_flos": 2444956052661120.0,
+  "train_batch_size": 2,
+  "trial_name": null,
+  "trial_params": null
+}

checkpoint-180/training_args.bin

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:34c4ca6d50f04301fb38588516a91421e14a8ad1ffddf12afdfd9ba35cd4b64e
+size 5777

checkpoint-190/README.md

@@ -0,0 +1,210 @@
+---
+base_model: unsloth/gemma-4-e2b-it-unsloth-bnb-4bit
+library_name: peft
+pipeline_tag: text-generation
+tags:
+- base_model:adapter:unsloth/gemma-4-e2b-it-unsloth-bnb-4bit
+- lora
+- sft
+- transformers
+- trl
+- unsloth
+---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **Developed by:** [More Information Needed]
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed]
+- **Finetuned from model [optional]:** [More Information Needed]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[More Information Needed]
+
+### Downstream Use [optional]
+
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+
+[More Information Needed]
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+[More Information Needed]
+
+## Training Details
+
+### Training Data
+
+<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+
+[More Information Needed]
+
+### Training Procedure
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
+- **Compute Region:** [More Information Needed]
+- **Carbon Emitted:** [More Information Needed]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]
+### Framework versions
+
+- PEFT 0.18.1

checkpoint-190/adapter_config.json

@@ -0,0 +1,50 @@
+{
+  "alora_invocation_tokens": null,
+  "alpha_pattern": {},
+  "arrow_config": null,
+  "auto_mapping": {
+    "base_model_class": "Gemma4ForConditionalGeneration",
+    "parent_library": "transformers.models.gemma4.modeling_gemma4",
+    "unsloth_fixed": true
+  },
+  "base_model_name_or_path": "unsloth/gemma-4-e2b-it-unsloth-bnb-4bit",
+  "bias": "none",
+  "corda_config": null,
+  "ensure_weight_tying": false,
+  "eva_config": null,
+  "exclude_modules": null,
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layer_replication": null,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 32,
+  "lora_bias": false,
+  "lora_dropout": 0.0,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "peft_version": "0.18.1",
+  "qalora_group_size": 16,
+  "r": 16,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "q_proj",
+    "gate_proj",
+    "v_proj",
+    "k_proj",
+    "down_proj",
+    "o_proj",
+    "up_proj"
+  ],
+  "target_parameters": null,
+  "task_type": "CAUSAL_LM",
+  "trainable_token_indices": null,
+  "use_dora": false,
+  "use_qalora": false,
+  "use_rslora": false
+}

checkpoint-190/adapter_model.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:dae7c101be06c818341a1b3354a5715c93ad40fc4c4700a81f0c71c0e699b82b
+size 124277728

checkpoint-190/chat_template.jinja

@@ -0,0 +1,351 @@
+{%- macro format_parameters(properties, required, filter_keys=false) -%}
+    {%- set standard_keys = ['description', 'type', 'properties', 'required', 'nullable'] -%}
+    {%- set ns = namespace(found_first=false) -%}
+    {%- for key, value in properties | dictsort -%}
+        {%- set add_comma = false -%}
+        {%- if not filter_keys or key not in standard_keys -%}
+            {%- if ns.found_first %},{% endif -%}
+            {%- set ns.found_first = true -%}
+            {{ key }}:{
+            {%- if value['description'] -%}
+                description:<|"|>{{ value['description'] }}<|"|>
+                {%- set add_comma = true -%}
+            {%- endif -%}
+            {%- if value['type'] | upper == 'STRING' -%}
+                {%- if value['enum'] -%}
+                    {%- if add_comma %},{%- else -%} {%- set add_comma = true -%} {% endif -%}
+                    enum:{{ format_argument(value['enum']) }}
+                {%- endif -%}
+            {%- elif value['type'] | upper == 'ARRAY' -%}
+                {%- if value['items'] is mapping and value['items'] -%}
+                    {%- if add_comma %},{%- else -%} {%- set add_comma = true -%} {% endif -%}
+                    items:{
+                    {%- set ns_items = namespace(found_first=false) -%}
+                    {%- for item_key, item_value in value['items'] | dictsort -%}
+                        {%- if item_value is not none -%}
+                            {%- if ns_items.found_first %},{% endif -%}
+                            {%- set ns_items.found_first = true -%}
+                            {%- if item_key == 'properties' -%}
+                                properties:{
+                                {%- if item_value is mapping -%}
+                                    {{- format_parameters(item_value, value['items']['required'] | default([])) -}}
+                                {%- endif -%}
+                                }
+                            {%- elif item_key == 'required' -%}
+                                required:[
+                                {%- for req_item in item_value -%}
+                                    <|"|>{{- req_item -}}<|"|>
+                                    {%- if not loop.last %},{% endif -%}
+                                {%- endfor -%}
+                                ]
+                            {%- elif item_key == 'type' -%}
+                                {%- if item_value is string -%}
+                                    type:{{ format_argument(item_value | upper) }}
+                                {%- else -%}
+                                    type:{{ format_argument(item_value | map('upper') | list) }}
+                                {%- endif -%}
+                            {%- else -%}
+                                {{ item_key }}:{{ format_argument(item_value) }}
+                            {%- endif -%}
+                        {%- endif -%}
+                    {%- endfor -%}
+                    }
+                {%- endif -%}
+            {%- endif -%}
+            {%- if value['nullable'] %}
+                {%- if add_comma %},{%- else -%} {%- set add_comma = true -%} {% endif -%}
+                nullable:true
+            {%- endif -%}
+            {%- if value['type'] | upper == 'OBJECT' -%}
+                {%- if value['properties'] is defined and value['properties'] is mapping -%}
+                    {%- if add_comma %},{%- else -%} {%- set add_comma = true -%} {% endif -%}
+                    properties:{
+                    {{- format_parameters(value['properties'], value['required'] | default([])) -}}
+                    }
+                {%- elif value is mapping -%}
+                    {%- if add_comma %},{%- else -%} {%- set add_comma = true -%} {% endif -%}
+                    properties:{
+                    {{- format_parameters(value, value['required'] | default([]), filter_keys=true) -}}
+                    }
+                {%- endif -%}
+                {%- if value['required'] -%}
+                    {%- if add_comma %},{%- else -%} {%- set add_comma = true -%} {% endif -%}
+                    required:[
+                    {%- for item in value['required'] | default([]) -%}
+                        <|"|>{{- item -}}<|"|>
+                        {%- if not loop.last %},{% endif -%}
+                    {%- endfor -%}
+                    ]
+                {%- endif -%}
+            {%- endif -%}
+            {%- if add_comma %},{%- else -%} {%- set add_comma = true -%} {% endif -%}
+            type:<|"|>{{ value['type'] | upper }}<|"|>}
+        {%- endif -%}
+    {%- endfor -%}
+{%- endmacro -%}
+{%- macro format_function_declaration(tool_data) -%}
+    declaration:{{- tool_data['function']['name'] -}}{description:<|"|>{{- tool_data['function']['description'] -}}<|"|>
+    {%- set params = tool_data['function']['parameters'] -%}
+    {%- if params -%}
+        ,parameters:{
+        {%- if params['properties'] -%}
+            properties:{ {{- format_parameters(params['properties'], params['required']) -}} },
+        {%- endif -%}
+        {%- if params['required'] -%}
+            required:[
+            {%- for item in params['required'] -%}
+                <|"|>{{- item -}}<|"|>
+                {{- ',' if not loop.last -}}
+            {%- endfor -%}
+            ],
+        {%- endif -%}
+        {%- if params['type'] -%}
+            type:<|"|>{{- params['type'] | upper -}}<|"|>}
+        {%- endif -%}
+    {%- endif -%}
+    {%- if 'response' in tool_data['function'] -%}
+        {%- set response_declaration = tool_data['function']['response'] -%}
+        ,response:{
+        {%- if response_declaration['description'] -%}
+            description:<|"|>{{- response_declaration['description'] -}}<|"|>,
+        {%- endif -%}
+        {%- if response_declaration['type'] | upper == 'OBJECT' -%}
+            type:<|"|>{{- response_declaration['type'] | upper -}}<|"|>}
+        {%- endif -%}
+    {%- endif -%}
+    }
+{%- endmacro -%}
+{%- macro format_argument(argument, escape_keys=True) -%}
+    {%- if argument is string -%}
+        {{- '<|"|>' + argument + '<|"|>' -}}
+    {%- elif argument is boolean -%}
+        {{- 'true' if argument else 'false' -}}
+    {%- elif argument is mapping -%}
+        {{- '{' -}}
+        {%- set ns = namespace(found_first=false) -%}
+        {%- for key, value in argument | dictsort -%}
+            {%- if ns.found_first %},{% endif -%}
+            {%- set ns.found_first = true -%}
+            {%- if escape_keys -%}
+                {{- '<|"|>' + key + '<|"|>' -}}
+            {%- else -%}
+                {{- key -}}
+            {%- endif -%}
+            :{{- format_argument(value, escape_keys=escape_keys) -}}
+        {%- endfor -%}
+        {{- '}' -}}
+    {%- elif argument is sequence -%}
+        {{- '[' -}}
+        {%- for item in argument -%}
+            {{- format_argument(item, escape_keys=escape_keys) -}}
+            {%- if not loop.last %},{% endif -%}
+        {%- endfor -%}
+        {{- ']' -}}
+    {%- else -%}
+        {{- argument -}}
+    {%- endif -%}
+{%- endmacro -%}
+{%- macro strip_thinking(text) -%}
+    {%- set ns = namespace(result='') -%}
+    {%- for part in text.split('<channel|>') -%}
+        {%- if '<|channel>' in part -%}
+            {%- set ns.result = ns.result + part.split('<|channel>')[0] -%}
+        {%- else -%}
+            {%- set ns.result = ns.result + part -%}
+        {%- endif -%}
+    {%- endfor -%}
+    {{- ns.result | trim -}}
+{%- endmacro -%}
+
+{%- macro format_tool_response_block(tool_name, response) -%}
+    {{- '<|tool_response>' -}}
+    {%- if response is mapping -%}
+        {{- 'response:' + tool_name + '{' -}}
+        {%- for key, value in response | dictsort -%}
+            {{- key -}}:{{- format_argument(value, escape_keys=False) -}}
+            {%- if not loop.last %},{% endif -%}
+        {%- endfor -%}
+        {{- '}' -}}
+    {%- else -%}
+        {{- 'response:' + tool_name + '{value:' + format_argument(response, escape_keys=False) + '}' -}}
+    {%- endif -%}
+    {{- '<tool_response|>' -}}
+{%- endmacro -%}
+
+{%- set ns = namespace(prev_message_type=None) -%}
+{%- set loop_messages = messages -%}
+{{- bos_token -}}
+{#- Handle System/Tool Definitions Block -#}
+{%- if (enable_thinking is defined and enable_thinking) or tools or messages[0]['role'] in ['system', 'developer'] -%}
+    {{- '<|turn>system\n' -}}
+    {#- Inject Thinking token at the very top of the FIRST system turn -#}
+    {%- if enable_thinking is defined and enable_thinking -%}
+        {{- '<|think|>\n' -}}
+        {%- set ns.prev_message_type = 'think' -%}
+    {%- endif -%}
+    {%- if messages[0]['role'] in ['system', 'developer'] -%}
+        {%- if messages[0]['content'] is string -%}
+            {{- messages[0]['content'] | trim -}}
+        {%- elif messages[0]['content'] is sequence -%}
+            {%- for item in messages[0]['content'] -%}
+                {{- item['text'] | trim + ' '-}}
+            {%- endfor -%}
+        {%- endif -%}
+        {%- set loop_messages = messages[1:] -%}
+    {%- endif -%}
+    {%- if tools -%}
+        {%- for tool in tools %}
+            {{- '<|tool>' -}}
+            {{- format_function_declaration(tool) | trim -}}
+            {{- '<tool|>' -}}
+        {%- endfor %}
+        {%- set ns.prev_message_type = 'tool' -%}
+    {%- endif -%}
+    {{- '<turn|>\n' -}}
+{%- endif %}
+
+{#- Pre-scan: find last user message index for reasoning guard -#}
+{%- set ns_turn = namespace(last_user_idx=-1) -%}
+{%- for i in range(loop_messages | length) -%}
+    {%- if loop_messages[i]['role'] == 'user' -%}
+        {%- set ns_turn.last_user_idx = i -%}
+    {%- endif -%}
+{%- endfor -%}
+
+{#- Loop through messages -#}
+{%- for message in loop_messages -%}
+    {%- if message['role'] != 'tool' -%}
+    {%- set ns.prev_message_type = None -%}
+    {%- set role = 'model' if message['role'] == 'assistant' else message['role'] -%}
+    {#- Detect continuation: suppress duplicate <|turn>model when previous non-tool message was also assistant -#}
+    {%- set prev_nt = namespace(role=None, found=false) -%}
+    {%- if loop.index0 > 0 -%}
+        {%- for j in range(loop.index0 - 1, -1, -1) -%}
+            {%- if not prev_nt.found -%}
+                {%- if loop_messages[j]['role'] != 'tool' -%}
+                    {%- set prev_nt.role = loop_messages[j]['role'] -%}
+                    {%- set prev_nt.found = true -%}
+                {%- endif -%}
+            {%- endif -%}
+        {%- endfor -%}
+    {%- endif -%}
+    {%- set continue_same_model_turn = (role == 'model' and prev_nt.role == 'assistant') -%}
+    {%- if not continue_same_model_turn -%}
+        {{- '<|turn>' + role + '\n' }}
+    {%- endif -%}
+
+    {#- Render reasoning/reasoning_content as thinking channel -#}
+    {%- set thinking_text = message.get('reasoning') or message.get('reasoning_content') -%}
+    {%- if thinking_text and loop.index0 > ns_turn.last_user_idx and message.get('tool_calls') -%}
+        {{- '<|channel>thought\n' + thinking_text + '\n<channel|>' -}}
+    {%- endif -%}
+
+            {%- if message['tool_calls'] -%}
+                {%- for tool_call in message['tool_calls'] -%}
+                    {%- set function = tool_call['function'] -%}
+                    {{- '<|tool_call>call:' + function['name'] + '{' -}}
+                    {%- if function['arguments'] is mapping -%}
+                        {%- set ns_args = namespace(found_first=false) -%}
+                        {%- for key, value in function['arguments'] | dictsort -%}
+                            {%- if ns_args.found_first %},{% endif -%}
+                            {%- set ns_args.found_first = true -%}
+                            {{- key -}}:{{- format_argument(value, escape_keys=False) -}}
+                        {%- endfor -%}
+                    {%- elif function['arguments'] is string -%}
+                        {{- function['arguments'] -}}
+                    {%- endif -%}
+                    {{- '}<tool_call|>' -}}
+                {%- endfor -%}
+                {%- set ns.prev_message_type = 'tool_call' -%}
+            {%- endif -%}
+
+            {%- set ns_tr_out = namespace(flag=false) -%}
+            {%- if message.get('tool_responses') -%}
+                {#- Legacy: tool_responses embedded on the assistant message (Google/Gemma native) -#}
+                {%- for tool_response in message['tool_responses'] -%}
+                    {{- format_tool_response_block(tool_response['name'] | default('unknown'), tool_response['response']) -}}
+                    {%- set ns_tr_out.flag = true -%}
+                    {%- set ns.prev_message_type = 'tool_response' -%}
+                {%- endfor -%}
+            {%- elif message.get('tool_calls') -%}
+                {#- OpenAI Chat Completions: forward-scan consecutive role:tool messages -#}
+                {%- set ns_tool_scan = namespace(stopped=false) -%}
+                {%- for k in range(loop.index0 + 1, loop_messages | length) -%}
+                    {%- if ns_tool_scan.stopped -%}
+                    {%- elif loop_messages[k]['role'] != 'tool' -%}
+                        {%- set ns_tool_scan.stopped = true -%}
+                    {%- else -%}
+                        {%- set follow = loop_messages[k] -%}
+                        {#- Resolve tool_call_id to function name -#}
+                        {%- set ns_tname = namespace(name=follow.get('name') | default('unknown')) -%}
+                        {%- for tc in message['tool_calls'] -%}
+                            {%- if tc.get('id') == follow.get('tool_call_id') -%}
+                                {%- set ns_tname.name = tc['function']['name'] -%}
+                            {%- endif -%}
+                        {%- endfor -%}
+                        {#- Handle content as string or content-parts array -#}
+                        {%- set tool_body = follow.get('content') -%}
+                        {%- if tool_body is string -%}
+                            {{- format_tool_response_block(ns_tname.name, tool_body) -}}
+                        {%- elif tool_body is sequence and tool_body is not string -%}
+                            {%- set ns_txt = namespace(s='') -%}
+                            {%- for part in tool_body -%}
+                                {%- if part.get('type') == 'text' -%}
+                                    {%- set ns_txt.s = ns_txt.s + (part.get('text') | default('')) -%}
+                                {%- endif -%}
+                            {%- endfor -%}
+                            {{- format_tool_response_block(ns_tname.name, ns_txt.s) -}}
+                        {%- else -%}
+                            {{- format_tool_response_block(ns_tname.name, tool_body) -}}
+                        {%- endif -%}
+                        {%- set ns_tr_out.flag = true -%}
+                        {%- set ns.prev_message_type = 'tool_response' -%}
+                    {%- endif -%}
+                {%- endfor -%}
+            {%- endif -%}
+
+            {%- set captured_content -%}
+            {%- if message['content'] is string -%}
+                {%- if role == 'model' -%}
+                    {{- strip_thinking(message['content']) -}}
+                {%- else -%}
+                    {{- message['content'] | trim -}}
+                {%- endif -%}
+            {%- elif message['content'] is sequence -%}
+                {%- for item in message['content'] -%}
+                    {%- if item['type'] == 'text' -%}
+                        {%- if role == 'model' -%}
+                            {{- strip_thinking(item['text']) -}}
+                        {%- else -%}
+                            {{- item['text'] | trim -}}
+                        {%- endif -%}
+                    {%- elif item['type'] == 'image' -%}
+                        {{- '<|image|>' -}}
+                        {%- set ns.prev_message_type = 'image' -%}
+                    {%- elif item['type'] == 'audio' -%}
+                        {{- '<|audio|>' -}}
+                        {%- set ns.prev_message_type = 'audio' -%}
+                    {%- elif item['type'] == 'video' -%}
+                        {{- '<|video|>' -}}
+                        {%- set ns.prev_message_type = 'video' -%}
+                    {%- endif -%}
+                {%- endfor -%}
+            {%- endif -%}
+            {%- endset -%}
+
+            {{- captured_content -}}
+            {%- set has_content = captured_content | trim | length > 0 -%}
+
+        {%- if ns.prev_message_type == 'tool_call' and not ns_tr_out.flag -%}
+            {{- '<|tool_response>' -}}
+        {%- elif not (ns_tr_out.flag and not has_content) -%}
+            {{- '<turn|>\n' -}}
+        {%- endif -%}
+    {%- endif -%}
+{%- endfor -%}
+
+{%- if add_generation_prompt -%}
+    {%- if ns.prev_message_type != 'tool_response' and ns.prev_message_type != 'tool_call' -%}
+        {{- '<|turn>model\n' -}}
+    {%- endif -%}
+{%- endif -%}

checkpoint-190/optimizer.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:b26ffa09ce09033bd748c71a5bd466483b607675e03fe146c587da6439440b9d
+size 52047117

checkpoint-190/processor_config.json

@@ -0,0 +1,75 @@
+{
+  "audio_ms_per_token": 40,
+  "audio_seq_length": 750,
+  "feature_extractor": {
+    "dither": 0.0,
+    "feature_extractor_type": "Gemma4AudioFeatureExtractor",
+    "feature_size": 128,
+    "fft_length": 512,
+    "fft_overdrive": false,
+    "frame_length": 320,
+    "hop_length": 160,
+    "input_scale_factor": 1.0,
+    "max_frequency": 8000.0,
+    "mel_floor": 0.001,
+    "min_frequency": 0.0,
+    "padding_side": "left",
+    "padding_value": 0.0,
+    "per_bin_mean": null,
+    "per_bin_stddev": null,
+    "preemphasis": 0.0,
+    "preemphasis_htk_flavor": true,
+    "return_attention_mask": true,
+    "sampling_rate": 16000
+  },
+  "image_processor": {
+    "do_convert_rgb": true,
+    "do_normalize": false,
+    "do_rescale": true,
+    "do_resize": true,
+    "image_mean": [
+      0.0,
+      0.0,
+      0.0
+    ],
+    "image_processor_type": "Gemma4ImageProcessor",
+    "image_seq_length": 280,
+    "image_std": [
+      1.0,
+      1.0,
+      1.0
+    ],
+    "max_soft_tokens": 280,
+    "patch_size": 16,
+    "pooling_kernel_size": 3,
+    "resample": 3,
+    "rescale_factor": 0.00392156862745098
+  },
+  "image_seq_length": 280,
+  "processor_class": "Gemma4Processor",
+  "video_processor": {
+    "do_convert_rgb": true,
+    "do_normalize": true,
+    "do_rescale": true,
+    "do_resize": true,
+    "do_sample_frames": true,
+    "image_mean": [
+      0.0,
+      0.0,
+      0.0
+    ],
+    "image_std": [
+      1.0,
+      1.0,
+      1.0
+    ],
+    "max_soft_tokens": 70,
+    "num_frames": 32,
+    "patch_size": 16,
+    "pooling_kernel_size": 3,
+    "resample": 3,
+    "rescale_factor": 0.00392156862745098,
+    "return_metadata": false,
+    "video_processor_type": "Gemma4VideoProcessor"
+  }
+}

checkpoint-190/rng_state.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:f1d565802a8e26c4e8a31328752b7a7fdc186d9401aa008e65697d0ad8c22e33
+size 14645

checkpoint-190/scaler.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:e582bf3c00963bd3fcaa4b162e161d1ea274c715ce05768df1a86c80c59a424e
+size 1383