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@@ -33,3 +33,5 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+checkpoint-40/tokenizer.json filter=lfs diff=lfs merge=lfs -text
+tokenizer.json filter=lfs diff=lfs merge=lfs -text

README.md

@@ -0,0 +1,196 @@
+---
+library_name: peft
+license: llama3.1
+base_model: meta-llama/Llama-3.1-8B-Instruct
+tags:
+- axolotl
+- base_model:adapter:meta-llama/Llama-3.1-8B-Instruct
+- lora
+- transformers
+datasets:
+- AIPixelMedia/astrid-dataset
+pipeline_tag: text-generation
+model-index:
+- name: outputs/astrid-llama-8b
+  results: []
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+[<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl)
+<details><summary>See axolotl config</summary>
+
+axolotl version: `0.13.0.dev0`
+```yaml
+base_model: meta-llama/Llama-3.1-8B-Instruct
+
+load_in_8bit: false
+
+load_in_4bit: true
+
+strict: false
+
+adapter: lora
+
+datasets:
+
+  - path: AIPixelMedia/astrid-dataset
+
+    data_files: "*formatted.jsonl"
+
+    type: alpaca
+
+dataset_prepared_path: last_run_prepared
+
+val_set_size: 0.1
+
+output_dir: ./outputs/astrid-llama-8b
+
+sequence_len: 2048
+
+sample_packing: true
+
+eval_sample_packing: false
+
+pad_to_sequence_len: true
+
+flash_attention: true
+
+seed: 35
+
+gradient_accumulation_steps: 4
+
+micro_batch_size: 2
+
+num_epochs: 20
+
+optimizer: paged_adamw_32bit
+
+learning_rate: 2e-5
+
+lr_scheduler: cosine
+
+lora_r: 16
+
+lora_alpha: 32
+
+lora_dropout: 0.2
+
+lora_target_modules:
+
+  - q_proj
+
+  - k_proj
+
+  - v_proj
+
+  - o_proj
+
+  - gate_proj
+
+  - up_proj
+
+  - down_proj
+
+lora_modules_to_save:
+
+  - lm_head
+
+merge_lora: false
+
+save_safetensors: true
+
+train_on_inputs: false
+
+group_by_length: true
+
+bf16: auto
+
+tf32: false
+
+gradient_checkpointing: true
+
+gradient_checkpointing_kwargs:
+
+  use_reentrant: false
+
+eval_steps: 5
+
+save_steps: 100
+
+early_stopping_patience: 2
+
+logging_steps: 5
+
+warmup_steps: 10
+
+weight_decay: 0.01
+
+special_tokens:
+
+  pad_token: "<|end_of_text|>"
+
+```
+
+</details><br>
+
+# outputs/astrid-llama-8b
+
+This model is a fine-tuned version of [meta-llama/Llama-3.1-8B-Instruct](https://huggingface.co/meta-llama/Llama-3.1-8B-Instruct) on the AIPixelMedia/astrid-dataset dataset.
+It achieves the following results on the evaluation set:
+- Loss: 2.3918
+- Memory/max Active (gib): 12.13
+- Memory/max Allocated (gib): 12.13
+- Memory/device Reserved (gib): 16.52
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 2e-05
+- train_batch_size: 2
+- eval_batch_size: 2
+- seed: 35
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 8
+- optimizer: Use OptimizerNames.PAGED_ADAMW with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: cosine
+- lr_scheduler_warmup_steps: 10
+- training_steps: 40
+
+### Training results
+
+| Training Loss | Epoch   | Step | Validation Loss | Active (gib) | Allocated (gib) | Reserved (gib) |
+|:-------------:|:-------:|:----:|:---------------:|:------------:|:---------------:|:--------------:|
+| No log        | 0       | 0    | 3.2546          | 11.95        | 11.95           | 12.15          |
+| 3.1725        | 1.8889  | 5    | 3.2149          | 12.13        | 12.13           | 17.46          |
+| 3.1171        | 3.4444  | 10   | 2.9429          | 12.13        | 12.13           | 16.52          |
+| 2.6355        | 5.0     | 15   | 2.6398          | 12.13        | 12.13           | 16.52          |
+| 2.3752        | 6.8889  | 20   | 2.5206          | 12.13        | 12.13           | 16.52          |
+| 2.1869        | 8.4444  | 25   | 2.4464          | 12.13        | 12.13           | 16.52          |
+| 2.0751        | 10.0    | 30   | 2.4187          | 12.13        | 12.13           | 16.52          |
+| 2.0616        | 11.8889 | 35   | 2.4084          | 12.13        | 12.13           | 16.52          |
+| 2.0263        | 13.4444 | 40   | 2.3918          | 12.13        | 12.13           | 16.52          |
+
+
+### Framework versions
+
+- PEFT 0.17.1
+- Transformers 4.57.0
+- Pytorch 2.7.1+cu126
+- Datasets 4.0.0
+- Tokenizers 0.22.1

adapter_config.json

@@ -0,0 +1,44 @@
+{
+  "alpha_pattern": {},
+  "auto_mapping": null,
+  "base_model_name_or_path": "meta-llama/Llama-3.1-8B-Instruct",
+  "bias": "none",
+  "corda_config": null,
+  "eva_config": null,
+  "exclude_modules": null,
+  "fan_in_fan_out": null,
+  "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": 0.2,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": [
+    "lm_head"
+  ],
+  "peft_type": "LORA",
+  "qalora_group_size": 16,
+  "r": 16,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "q_proj",
+    "o_proj",
+    "v_proj",
+    "up_proj",
+    "gate_proj",
+    "k_proj",
+    "down_proj"
+  ],
+  "target_parameters": [],
+  "task_type": "CAUSAL_LM",
+  "trainable_token_indices": null,
+  "use_dora": false,
+  "use_qalora": false,
+  "use_rslora": false
+}

adapter_model.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:535433db2d800cc07aaff86636d89dfa137535dfb7d563e27041ace93a9fdace
+size 1218505504

chat_template.jinja

@@ -0,0 +1,109 @@
+{{- bos_token }}
+{%- if custom_tools is defined %}
+    {%- set tools = custom_tools %}
+{%- endif %}
+{%- if not tools_in_user_message is defined %}
+    {%- set tools_in_user_message = true %}
+{%- endif %}
+{%- if not date_string is defined %}
+    {%- set date_string = "26 Jul 2024" %}
+{%- endif %}
+{%- if not tools is defined %}
+    {%- set tools = none %}
+{%- endif %}
+
+{#- This block extracts the system message, so we can slot it into the right place. #}
+{%- if messages[0]['role'] == 'system' %}
+    {%- set system_message = messages[0]['content']|trim %}
+    {%- set messages = messages[1:] %}
+{%- else %}
+    {%- set system_message = "" %}
+{%- endif %}
+
+{#- System message + builtin tools #}
+{{- "<|start_header_id|>system<|end_header_id|>\n\n" }}
+{%- if builtin_tools is defined or tools is not none %}
+    {{- "Environment: ipython\n" }}
+{%- endif %}
+{%- if builtin_tools is defined %}
+    {{- "Tools: " + builtin_tools | reject('equalto', 'code_interpreter') | join(", ") + "\n\n"}}
+{%- endif %}
+{{- "Cutting Knowledge Date: December 2023\n" }}
+{{- "Today Date: " + date_string + "\n\n" }}
+{%- if tools is not none and not tools_in_user_message %}
+    {{- "You have access to the following functions. To call a function, please respond with JSON for a function call." }}
+    {{- 'Respond in the format {"name": function name, "parameters": dictionary of argument name and its value}.' }}
+    {{- "Do not use variables.\n\n" }}
+    {%- for t in tools %}
+        {{- t | tojson(indent=4) }}
+        {{- "\n\n" }}
+    {%- endfor %}
+{%- endif %}
+{{- system_message }}
+{{- "<|eot_id|>" }}
+
+{#- Custom tools are passed in a user message with some extra guidance #}
+{%- if tools_in_user_message and not tools is none %}
+    {#- Extract the first user message so we can plug it in here #}
+    {%- if messages | length != 0 %}
+        {%- set first_user_message = messages[0]['content']|trim %}
+        {%- set messages = messages[1:] %}
+    {%- else %}
+        {{- raise_exception("Cannot put tools in the first user message when there's no first user message!") }}
+{%- endif %}
+    {{- '<|start_header_id|>user<|end_header_id|>\n\n' -}}
+    {{- "Given the following functions, please respond with a JSON for a function call " }}
+    {{- "with its proper arguments that best answers the given prompt.\n\n" }}
+    {{- 'Respond in the format {"name": function name, "parameters": dictionary of argument name and its value}.' }}
+    {{- "Do not use variables.\n\n" }}
+    {%- for t in tools %}
+        {{- t | tojson(indent=4) }}
+        {{- "\n\n" }}
+    {%- endfor %}
+    {{- first_user_message + "<|eot_id|>"}}
+{%- endif %}
+
+{%- for message in messages %}
+    {%- if not (message.role == 'ipython' or message.role == 'tool' or 'tool_calls' in message) %}
+        {{- '<|start_header_id|>' + message['role'] + '<|end_header_id|>\n\n'+ message['content'] | trim + '<|eot_id|>' }}
+    {%- elif 'tool_calls' in message %}
+        {%- if not message.tool_calls|length == 1 %}
+            {{- raise_exception("This model only supports single tool-calls at once!") }}
+        {%- endif %}
+        {%- set tool_call = message.tool_calls[0].function %}
+        {%- if builtin_tools is defined and tool_call.name in builtin_tools %}
+            {{- '<|start_header_id|>assistant<|end_header_id|>\n\n' -}}
+            {{- "<|python_tag|>" + tool_call.name + ".call(" }}
+            {%- for arg_name, arg_val in tool_call.arguments | items %}
+                {{- arg_name + '="' + arg_val + '"' }}
+                {%- if not loop.last %}
+                    {{- ", " }}
+                {%- endif %}
+                {%- endfor %}
+            {{- ")" }}
+        {%- else  %}
+            {{- '<|start_header_id|>assistant<|end_header_id|>\n\n' -}}
+            {{- '{"name": "' + tool_call.name + '", ' }}
+            {{- '"parameters": ' }}
+            {{- tool_call.arguments | tojson }}
+            {{- "}" }}
+        {%- endif %}
+        {%- if builtin_tools is defined %}
+            {#- This means we're in ipython mode #}
+            {{- "<|eom_id|>" }}
+        {%- else %}
+            {{- "<|eot_id|>" }}
+        {%- endif %}
+    {%- elif message.role == "tool" or message.role == "ipython" %}
+        {{- "<|start_header_id|>ipython<|end_header_id|>\n\n" }}
+        {%- if message.content is mapping or message.content is iterable %}
+            {{- message.content | tojson }}
+        {%- else %}
+            {{- message.content }}
+        {%- endif %}
+        {{- "<|eot_id|>" }}
+    {%- endif %}
+{%- endfor %}
+{%- if add_generation_prompt %}
+    {{- '<|start_header_id|>assistant<|end_header_id|>\n\n' }}
+{%- endif %}

checkpoint-40/README.md

@@ -0,0 +1,208 @@
+---
+base_model: meta-llama/Llama-3.1-8B-Instruct
+library_name: peft
+pipeline_tag: text-generation
+tags:
+- axolotl
+- base_model:adapter:meta-llama/Llama-3.1-8B-Instruct
+- lora
+- transformers
+---
+
+# 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 0.17.1

checkpoint-40/adapter_config.json

@@ -0,0 +1,44 @@
+{
+  "alpha_pattern": {},
+  "auto_mapping": null,
+  "base_model_name_or_path": "meta-llama/Llama-3.1-8B-Instruct",
+  "bias": "none",
+  "corda_config": null,
+  "eva_config": null,
+  "exclude_modules": null,
+  "fan_in_fan_out": null,
+  "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": 0.2,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": [
+    "lm_head"
+  ],
+  "peft_type": "LORA",
+  "qalora_group_size": 16,
+  "r": 16,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "q_proj",
+    "o_proj",
+    "v_proj",
+    "up_proj",
+    "gate_proj",
+    "k_proj",
+    "down_proj"
+  ],
+  "target_parameters": [],
+  "task_type": "CAUSAL_LM",
+  "trainable_token_indices": null,
+  "use_dora": false,
+  "use_qalora": false,
+  "use_rslora": false
+}

checkpoint-40/adapter_model.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:535433db2d800cc07aaff86636d89dfa137535dfb7d563e27041ace93a9fdace
+size 1218505504

checkpoint-40/chat_template.jinja

@@ -0,0 +1,109 @@
+{{- bos_token }}
+{%- if custom_tools is defined %}
+    {%- set tools = custom_tools %}
+{%- endif %}
+{%- if not tools_in_user_message is defined %}
+    {%- set tools_in_user_message = true %}
+{%- endif %}
+{%- if not date_string is defined %}
+    {%- set date_string = "26 Jul 2024" %}
+{%- endif %}
+{%- if not tools is defined %}
+    {%- set tools = none %}
+{%- endif %}
+
+{#- This block extracts the system message, so we can slot it into the right place. #}
+{%- if messages[0]['role'] == 'system' %}
+    {%- set system_message = messages[0]['content']|trim %}
+    {%- set messages = messages[1:] %}
+{%- else %}
+    {%- set system_message = "" %}
+{%- endif %}
+
+{#- System message + builtin tools #}
+{{- "<|start_header_id|>system<|end_header_id|>\n\n" }}
+{%- if builtin_tools is defined or tools is not none %}
+    {{- "Environment: ipython\n" }}
+{%- endif %}
+{%- if builtin_tools is defined %}
+    {{- "Tools: " + builtin_tools | reject('equalto', 'code_interpreter') | join(", ") + "\n\n"}}
+{%- endif %}
+{{- "Cutting Knowledge Date: December 2023\n" }}
+{{- "Today Date: " + date_string + "\n\n" }}
+{%- if tools is not none and not tools_in_user_message %}
+    {{- "You have access to the following functions. To call a function, please respond with JSON for a function call." }}
+    {{- 'Respond in the format {"name": function name, "parameters": dictionary of argument name and its value}.' }}
+    {{- "Do not use variables.\n\n" }}
+    {%- for t in tools %}
+        {{- t | tojson(indent=4) }}
+        {{- "\n\n" }}
+    {%- endfor %}
+{%- endif %}
+{{- system_message }}
+{{- "<|eot_id|>" }}
+
+{#- Custom tools are passed in a user message with some extra guidance #}
+{%- if tools_in_user_message and not tools is none %}
+    {#- Extract the first user message so we can plug it in here #}
+    {%- if messages | length != 0 %}
+        {%- set first_user_message = messages[0]['content']|trim %}
+        {%- set messages = messages[1:] %}
+    {%- else %}
+        {{- raise_exception("Cannot put tools in the first user message when there's no first user message!") }}
+{%- endif %}
+    {{- '<|start_header_id|>user<|end_header_id|>\n\n' -}}
+    {{- "Given the following functions, please respond with a JSON for a function call " }}
+    {{- "with its proper arguments that best answers the given prompt.\n\n" }}
+    {{- 'Respond in the format {"name": function name, "parameters": dictionary of argument name and its value}.' }}
+    {{- "Do not use variables.\n\n" }}
+    {%- for t in tools %}
+        {{- t | tojson(indent=4) }}
+        {{- "\n\n" }}
+    {%- endfor %}
+    {{- first_user_message + "<|eot_id|>"}}
+{%- endif %}
+
+{%- for message in messages %}
+    {%- if not (message.role == 'ipython' or message.role == 'tool' or 'tool_calls' in message) %}
+        {{- '<|start_header_id|>' + message['role'] + '<|end_header_id|>\n\n'+ message['content'] | trim + '<|eot_id|>' }}
+    {%- elif 'tool_calls' in message %}
+        {%- if not message.tool_calls|length == 1 %}
+            {{- raise_exception("This model only supports single tool-calls at once!") }}
+        {%- endif %}
+        {%- set tool_call = message.tool_calls[0].function %}
+        {%- if builtin_tools is defined and tool_call.name in builtin_tools %}
+            {{- '<|start_header_id|>assistant<|end_header_id|>\n\n' -}}
+            {{- "<|python_tag|>" + tool_call.name + ".call(" }}
+            {%- for arg_name, arg_val in tool_call.arguments | items %}
+                {{- arg_name + '="' + arg_val + '"' }}
+                {%- if not loop.last %}
+                    {{- ", " }}
+                {%- endif %}
+                {%- endfor %}
+            {{- ")" }}
+        {%- else  %}
+            {{- '<|start_header_id|>assistant<|end_header_id|>\n\n' -}}
+            {{- '{"name": "' + tool_call.name + '", ' }}
+            {{- '"parameters": ' }}
+            {{- tool_call.arguments | tojson }}
+            {{- "}" }}
+        {%- endif %}
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+        {%- if message.content is mapping or message.content is iterable %}
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+        {%- else %}
+            {{- message.content }}
+        {%- endif %}
+        {{- "<|eot_id|>" }}
+    {%- endif %}
+{%- endfor %}
+{%- if add_generation_prompt %}
+    {{- '<|start_header_id|>assistant<|end_header_id|>\n\n' }}
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+size 7313

config.json

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+{
+  "architectures": [
+    "LlamaForCausalLM"
+  ],
+  "attention_bias": false,
+  "attention_dropout": 0.0,
+  "bos_token_id": 128000,
+  "dtype": "bfloat16",
+  "eos_token_id": 128009,
+  "head_dim": 128,
+  "hidden_act": "silu",
+  "hidden_size": 4096,
+  "initializer_range": 0.02,
+  "intermediate_size": 14336,
+  "max_position_embeddings": 131072,
+  "mlp_bias": false,
+  "model_type": "llama",
+  "num_attention_heads": 32,
+  "num_hidden_layers": 32,
+  "num_key_value_heads": 8,
+  "pretraining_tp": 1,
+  "quantization_config": {
+    "_load_in_4bit": true,
+    "_load_in_8bit": false,
+    "bnb_4bit_compute_dtype": "float32",
+    "bnb_4bit_quant_storage": "uint8",
+    "bnb_4bit_quant_type": "fp4",
+    "bnb_4bit_use_double_quant": false,
+    "llm_int8_enable_fp32_cpu_offload": false,
+    "llm_int8_has_fp16_weight": false,
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+    "llm_int8_threshold": 6.0,
+    "load_in_4bit": true,
+    "load_in_8bit": false,
+    "quant_method": "bitsandbytes"
+  },
+  "rms_norm_eps": 1e-05,
+  "rope_scaling": {
+    "factor": 8.0,
+    "high_freq_factor": 4.0,
+    "low_freq_factor": 1.0,
+    "original_max_position_embeddings": 8192,
+    "rope_type": "llama3"
+  },
+  "rope_theta": 500000.0,
+  "tie_word_embeddings": false,
+  "transformers_version": "4.57.0",
+  "use_cache": false,
+  "vocab_size": 128256
+}

debug.log

@@ -0,0 +1,364 @@
+[2025-11-25 02:20:44,846] [DEBUG] [axolotl.utils.config.resolve_dtype:66] [PID:3847] bf16 support detected, enabling for this configuration.
+[2025-11-25 02:20:44,921] [DEBUG] [axolotl.utils.config.log_gpu_memory_usage:127] [PID:3847] baseline 0.000GB ()
+[2025-11-25 02:20:44,921] [INFO] [axolotl.cli.config.load_cfg:248] [PID:3847] config:
+{
+  "activation_offloading": false,
+  "adapter": "lora",
+  "axolotl_config_path": "config.yaml",
+  "base_model": "meta-llama/Llama-3.1-8B-Instruct",
+  "base_model_config": "meta-llama/Llama-3.1-8B-Instruct",
+  "batch_size": 8,
+  "bf16": true,
+  "capabilities": {
+    "bf16": true,
+    "compute_capability": "sm_90",
+    "fp8": false,
+    "n_gpu": 1,
+    "n_node": 1
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+  "context_parallel_size": 1,
+  "dataloader_num_workers": 1,
+  "dataloader_pin_memory": true,
+  "dataloader_prefetch_factor": 256,
+  "dataset_prepared_path": "last_run_prepared",
+  "dataset_processes": 24,
+  "datasets": [
+    {
+      "data_files": "*formatted.jsonl",
+      "message_property_mappings": {
+        "content": "content",
+        "role": "role"
+      },
+      "path": "AIPixelMedia/astrid-dataset",
+      "trust_remote_code": false,
+      "type": "alpaca"
+    }
+  ],
+  "ddp": false,
+  "device": "cuda:0",
+  "dion_rank_fraction": 1.0,
+  "dion_rank_multiple_of": 1,
+  "early_stopping_patience": 2,
+  "env_capabilities": {
+    "torch_version": "2.7.1"
+  },
+  "eval_batch_size": 2,
+  "eval_causal_lm_metrics": [
+    "sacrebleu",
+    "comet",
+    "ter",
+    "chrf"
+  ],
+  "eval_max_new_tokens": 128,
+  "eval_sample_packing": false,
+  "eval_steps": 5,
+  "eval_table_size": 0,
+  "experimental_skip_move_to_device": true,
+  "flash_attention": true,
+  "fp16": false,
+  "gradient_accumulation_steps": 4,
+  "gradient_checkpointing": true,
+  "gradient_checkpointing_kwargs": {
+    "use_reentrant": false
+  },
+  "group_by_length": true,
+  "include_tkps": true,
+  "is_llama_derived_model": true,
+  "learning_rate": 2e-05,
+  "lisa_layers_attribute": "model.layers",
+  "load_best_model_at_end": false,
+  "load_in_4bit": true,
+  "load_in_8bit": false,
+  "local_rank": 0,
+  "logging_steps": 5,
+  "lora_alpha": 32,
+  "lora_dropout": 0.2,
+  "lora_modules_to_save": [
+    "lm_head"
+  ],
+  "lora_r": 16,
+  "lora_target_modules": [
+    "q_proj",
+    "k_proj",
+    "v_proj",
+    "o_proj",
+    "gate_proj",
+    "up_proj",
+    "down_proj"
+  ],
+  "loraplus_lr_embedding": 1e-06,
+  "lr_scheduler": "cosine",
+  "mean_resizing_embeddings": false,
+  "merge_lora": false,
+  "micro_batch_size": 2,
+  "model_config_type": "llama",
+  "num_epochs": 20.0,
+  "optimizer": "paged_adamw_32bit",
+  "output_dir": "./outputs/astrid-llama-8b",
+  "pad_to_sequence_len": true,
+  "pretrain_multipack_attn": true,
+  "profiler_steps_start": 0,
+  "qlora_sharded_model_loading": false,
+  "ray_num_workers": 1,
+  "remove_unused_columns": false,
+  "resources_per_worker": {
+    "GPU": 1
+  },
+  "sample_packing": true,
+  "sample_packing_bin_size": 200,
+  "sample_packing_group_size": 100000,
+  "save_only_model": false,
+  "save_safetensors": true,
+  "save_steps": 100,
+  "seed": 35,
+  "sequence_len": 2048,
+  "shuffle_before_merging_datasets": false,
+  "shuffle_merged_datasets": true,
+  "skip_prepare_dataset": false,
+  "special_tokens": {
+    "pad_token": "<|end_of_text|>"
+  },
+  "streaming_multipack_buffer_size": 10000,
+  "strict": false,
+  "tensor_parallel_size": 1,
+  "tf32": false,
+  "tiled_mlp_use_original_mlp": true,
+  "tokenizer_config": "meta-llama/Llama-3.1-8B-Instruct",
+  "tokenizer_save_jinja_files": true,
+  "torch_dtype": "torch.bfloat16",
+  "train_on_inputs": false,
+  "trl": {
+    "log_completions": false,
+    "mask_truncated_completions": false,
+    "ref_model_mixup_alpha": 0.9,
+    "ref_model_sync_steps": 64,
+    "scale_rewards": true,
+    "sync_ref_model": false,
+    "use_vllm": false,
+    "vllm_server_host": "0.0.0.0",
+    "vllm_server_port": 8000
+  },
+  "use_ray": false,
+  "val_set_size": 0.1,
+  "vllm": {
+    "device": "auto",
+    "dtype": "auto",
+    "gpu_memory_utilization": 0.9,
+    "host": "0.0.0.0",
+    "port": 8000
+  },
+  "warmup_steps": 10,
+  "weight_decay": 0.01,
+  "world_size": 1
+}
+[2025-11-25 02:20:45,359] [DEBUG] [axolotl.loaders.tokenizer.load_tokenizer:278] [PID:3847] EOS: 128009 / <|eot_id|>
+[2025-11-25 02:20:45,359] [DEBUG] [axolotl.loaders.tokenizer.load_tokenizer:279] [PID:3847] BOS: 128000 / <|begin_of_text|>
+[2025-11-25 02:20:45,360] [DEBUG] [axolotl.loaders.tokenizer.load_tokenizer:280] [PID:3847] PAD: 128001 / <|end_of_text|>
+[2025-11-25 02:20:45,360] [DEBUG] [axolotl.loaders.tokenizer.load_tokenizer:281] [PID:3847] UNK: None / None
+[2025-11-25 02:20:45,361] [INFO] [axolotl.utils.data.shared.load_preprocessed_dataset:476] [PID:3847] Unable to find prepared dataset in last_run_prepared/d6f798814894ac4627709b4d3b576758
+[2025-11-25 02:20:45,361] [INFO] [axolotl.utils.data.sft._load_raw_datasets:320] [PID:3847] Loading raw datasets...
+[2025-11-25 02:20:45,361] [WARNING] [axolotl.utils.data.sft._load_raw_datasets:322] [PID:3847] Processing datasets during training can lead to VRAM instability. Please pre-process your dataset using `axolotl preprocess path/to/config.yml`.
+
+
+
+[2025-11-25 02:20:46,223] [INFO] [axolotl.utils.data.wrappers.get_dataset_wrapper:87] [PID:3847] Loading dataset: AIPixelMedia/astrid-dataset with base_type: alpaca and prompt_style: None
+
+[2025-11-25 02:20:49,511] [INFO] [axolotl.utils.data.utils.handle_long_seq_in_dataset:218] [PID:3847] min_input_len: 164
+[2025-11-25 02:20:49,514] [INFO] [axolotl.utils.data.utils.handle_long_seq_in_dataset:220] [PID:3847] max_input_len: 195
+
+
+
+
+
+[2025-11-25 02:20:51,464] [DEBUG] [axolotl.utils.trainer.calculate_total_num_steps:404] [PID:3847] total_num_tokens: 34_394
+[2025-11-25 02:20:51,466] [DEBUG] [axolotl.utils.trainer.calculate_total_num_steps:422] [PID:3847] `total_supervised_tokens: 4_111`
+[2025-11-25 02:20:52,510] [DEBUG] [axolotl.utils.samplers.multipack.__len__:458] [PID:3847] generate_batches time: 0.4545629024505615
+[2025-11-25 02:20:52,977] [DEBUG] [axolotl.utils.samplers.multipack.__len__:458] [PID:3847] generate_batches time: 0.46656036376953125
+[2025-11-25 02:20:53,454] [DEBUG] [axolotl.utils.samplers.multipack.__len__:458] [PID:3847] generate_batches time: 0.47722506523132324
+[2025-11-25 02:20:53,916] [DEBUG] [axolotl.utils.samplers.multipack.__len__:458] [PID:3847] generate_batches time: 0.46124815940856934
+[2025-11-25 02:20:53,940] [INFO] [axolotl.utils.samplers.multipack.calc_min_len:434] [PID:3847] gather_len_batches: [9]
+[2025-11-25 02:20:53,940] [DEBUG] [axolotl.utils.trainer.calculate_total_num_steps:481] [PID:3847] data_loader_len: 2
+[2025-11-25 02:20:53,940] [INFO] [axolotl.utils.trainer.calc_sample_packing_eff_est:497] [PID:3847] sample_packing_eff_est across ranks: [0.9329969618055556]
+[2025-11-25 02:20:53,940] [DEBUG] [axolotl.utils.trainer.calculate_total_num_steps:509] [PID:3847] sample_packing_eff_est: 0.94
+[2025-11-25 02:20:53,941] [DEBUG] [axolotl.utils.trainer.calculate_total_num_steps:520] [PID:3847] total_num_steps: 40
+[2025-11-25 02:20:53,941] [INFO] [axolotl.utils.data.sft._prepare_standard_dataset:121] [PID:3847] Maximum number of steps set at 40
+[2025-11-25 02:20:53,975] [DEBUG] [axolotl.train.setup_model_and_tokenizer:65] [PID:3847] Loading tokenizer... meta-llama/Llama-3.1-8B-Instruct
+[2025-11-25 02:20:54,362] [DEBUG] [axolotl.loaders.tokenizer.load_tokenizer:278] [PID:3847] EOS: 128009 / <|eot_id|>
+[2025-11-25 02:20:54,363] [DEBUG] [axolotl.loaders.tokenizer.load_tokenizer:279] [PID:3847] BOS: 128000 / <|begin_of_text|>
+[2025-11-25 02:20:54,363] [DEBUG] [axolotl.loaders.tokenizer.load_tokenizer:280] [PID:3847] PAD: 128001 / <|end_of_text|>
+[2025-11-25 02:20:54,363] [DEBUG] [axolotl.loaders.tokenizer.load_tokenizer:281] [PID:3847] UNK: None / None
+[2025-11-25 02:20:54,363] [DEBUG] [axolotl.train.setup_model_and_tokenizer:74] [PID:3847] Loading model
+[2025-11-25 02:20:54,401] [DEBUG] [axolotl.monkeypatch.transformers.trainer_loss_calc.patch_evaluation_loop:87] [PID:3847] Patched Trainer.evaluation_loop with nanmean loss calculation
+[2025-11-25 02:20:54,404] [DEBUG] [axolotl.monkeypatch.transformers.trainer_loss_calc.patch_maybe_log_save_evaluate:138] [PID:3847] Patched Trainer._maybe_log_save_evaluate with nanmean loss calculation
+[2025-11-25 02:20:54,405] [INFO] [axolotl.loaders.patch_manager._apply_multipack_patches:301] [PID:3847] Applying multipack dataloader patch for sample packing...
+
+[2025-11-25 02:21:19,888] [INFO] [axolotl.loaders.model._prepare_model_for_quantization:863] [PID:3847] converting PEFT model w/ prepare_model_for_kbit_training
+[2025-11-25 02:21:19,891] [INFO] [axolotl.loaders.model._configure_embedding_dtypes:345] [PID:3847] Converting modules to torch.bfloat16
+[2025-11-25 02:21:19,894] [DEBUG] [axolotl.loaders.model.log_gpu_memory_usage:127] [PID:3847] Memory usage after model load 8.657GB (+8.657GB allocated, +9.924GB reserved)
+trainable params: 567,279,616 || all params: 8,597,540,864 || trainable%: 6.5982
+[2025-11-25 02:21:20,327] [DEBUG] [axolotl.loaders.model.log_gpu_memory_usage:127] [PID:3847] after adapters 6.813GB (+6.813GB allocated, +10.080GB reserved)
+[2025-11-25 02:21:25,049] [INFO] [axolotl.train.save_initial_configs:398] [PID:3847] Pre-saving adapter config to ./outputs/astrid-llama-8b...
+[2025-11-25 02:21:25,053] [INFO] [axolotl.train.save_initial_configs:402] [PID:3847] Pre-saving tokenizer to ./outputs/astrid-llama-8b...
+[2025-11-25 02:21:25,237] [INFO] [axolotl.train.save_initial_configs:407] [PID:3847] Pre-saving model config to ./outputs/astrid-llama-8b...
+[2025-11-25 02:21:25,242] [INFO] [axolotl.train.execute_training:196] [PID:3847] Starting trainer...
+[2025-11-25 02:21:26,800] [DEBUG] [axolotl.utils.samplers.multipack.__len__:458] [PID:3847] generate_batches time: 0.6591596603393555
+[2025-11-25 02:21:27,432] [DEBUG] [axolotl.utils.samplers.multipack.__len__:458] [PID:3847] generate_batches time: 0.6290566921234131
+[2025-11-25 02:21:28,054] [DEBUG] [axolotl.utils.samplers.multipack.__len__:458] [PID:3847] generate_batches time: 0.6219644546508789
+[2025-11-25 02:21:28,676] [DEBUG] [axolotl.utils.samplers.multipack.__len__:458] [PID:3847] generate_batches time: 0.6212875843048096
+[2025-11-25 02:21:28,677] [INFO] [axolotl.utils.samplers.multipack.calc_min_len:434] [PID:3847] gather_len_batches: [9]
+
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 12%|███████████████▌                                                                                                            | 5/40 [00:20<01:51,  3.19s/it]
+
+
                                                                                                                                                                
 15%|██████████████████▌                                                                                                         | 6/40 [00:21<01:50,  3.24s/it]
 18%|█████████████████████▋                                                                                                      | 7/40 [00:25<01:58,  3.58s/it]
 20%|████████████████████████▊                                                                                                   | 8/40 [00:28<01:46,  3.34s/it]
 22%|███████████████████████████▉                                                                                                | 9/40 [00:28<01:15,  2.45s/it]
 25%|██████████████████████████████▊                                                                                            | 10/40 [00:33<01:31,  3.07s/it]
                                                                                                                                                                
+
 25%|██████████████████████████████▊                                                                                            | 10/40 [00:33<01:31,  3.07s/it][2025-11-25 02:22:02,136] [INFO] [axolotl.core.trainers.base.evaluate:376] [PID:3847] Running evaluation step...
+
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+
 18%|██████████████████████▌                                                                                                     | 2/11 [00:00<00:00,  9.35it/s]
+
 27%|█████████████████████████████████▊                                                                                          | 3/11 [00:00<00:01,  6.57it/s]
+
 36%|█████████████████████████████████████████████                                                                               | 4/11 [00:00<00:01,  5.70it/s]
+
 45%|████████████████████████████████████████████████████████▎                                                                   | 5/11 [00:00<00:01,  4.74it/s]
+
 55%|███████████████████████████████████████████████████████████████████▋                                                        | 6/11 [00:01<00:01,  4.84it/s]
+
 64%|██████████████████████████████████████████████████████████████████████████████▉                                             | 7/11 [00:01<00:00,  4.78it/s]
+
 73%|██████████████████████████████████████████████████████████████████████████████████████████▏                                 | 8/11 [00:01<00:00,  4.74it/s]
+
 82%|█████████████████████████████████████████████████████████████████████████████████████████████████████▍                      | 9/11 [00:01<00:00,  4.44it/s]
+
 91%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████▊           | 10/11 [00:02<00:00,  4.61it/s]
+
                                                                                                                                                                
+
                                                                                                                                                                
+
 25%|██████████████████████████████▊                                                                                            | 10/40 [00:35<01:31,  3.07s/it]
+
+
                                                                                                                                                                
 28%|█████████████████████████████████▊                                                                                         | 11/40 [00:38<01:49,  3.77s/it]
 30%|████████████████████████████████████▉                                                                                      | 12/40 [00:39<01:19,  2.85s/it]
 32%|███████████████████████████████████████▉                                                                                   | 13/40 [00:43<01:28,  3.28s/it]
 35%|███████████████████████████████████████████                                                                                | 14/40 [00:46<01:21,  3.13s/it]
 38%|██████████████████████████████████████████████▏                                                                            | 15/40 [00:47<00:58,  2.34s/it]
                                                                                                                                                                
+
 38%|██████████████████████████████████████████████▏                                                                            | 15/40 [00:47<00:58,  2.34s/it][2025-11-25 02:22:15,792] [INFO] [axolotl.core.trainers.base.evaluate:376] [PID:3847] Running evaluation step...
+
+
  0%|                                                                                                                                    | 0/11 [00:00<?, ?it/s]
+
 18%|██████████████████████▌                                                                                                     | 2/11 [00:00<00:00,  9.36it/s]
+
 27%|█████████████████████████████████▊                                                                                          | 3/11 [00:00<00:01,  6.59it/s]
+
 36%|█████████████████████████████████████████████                                                                               | 4/11 [00:00<00:01,  5.69it/s]
+
 45%|████████████████████████████████████████████████████████▎                                                                   | 5/11 [00:00<00:01,  4.73it/s]
+
 55%|█████████████████████████████████████████████████████████���█████████▋                                                        | 6/11 [00:01<00:01,  4.83it/s]
+
 64%|██████████████████████████████████████████████████████████████████████████████▉                                             | 7/11 [00:01<00:00,  4.77it/s]
+
 73%|██████████████████████████████████████████████████████████████████████████████████████████▏                                 | 8/11 [00:01<00:00,  4.73it/s]
+
 82%|█████████████████████████████████████████████████████████████████████████████████████████████████████▍                      | 9/11 [00:01<00:00,  4.44it/s]
+
 91%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████▊           | 10/11 [00:02<00:00,  4.61it/s]
+
                                                                                                                                                                
+
                                                                                                                                                                
+
 38%|██████████████████████████████████████████████▏                                                                            | 15/40 [00:49<00:58,  2.34s/it]
+
+
                                                                                                                                                                
 40%|█████████████████████████████████████████████████▏                                                                         | 16/40 [00:53<01:29,  3.72s/it]
 42%|████████████████████████████████████████████████████▎                                                                      | 17/40 [00:56<01:19,  3.44s/it]
 45%|███████████████████████████████████████████████████████▎                                                                   | 18/40 [00:57<00:56,  2.55s/it]
 48%|██████████████████████████████████████████████████████████▍                                                                | 19/40 [01:01<01:04,  3.07s/it]
 50%|█████████████████████████████████████████████████████████████▌                                                             | 20/40 [01:04<00:59,  2.98s/it]
                                                                                                                                                                
+
 50%|█████████████████████████████████████████████████████████████▌                                                             | 20/40 [01:04<00:59,  2.98s/it][2025-11-25 02:22:33,042] [INFO] [axolotl.core.trainers.base.evaluate:376] [PID:3847] Running evaluation step...
+
+
  0%|                                                                                                                                    | 0/11 [00:00<?, ?it/s]
+
 18%|██████████████████████▌                                                                                                     | 2/11 [00:00<00:00,  9.37it/s]
+
 27%|█████████████████████████████████▊                                                                                          | 3/11 [00:00<00:01,  6.59it/s]
+
 36%|█████████████████████████████████████████████                                                                               | 4/11 [00:00<00:01,  5.70it/s]
+
 45%|████████████████████████████████████████████████████████▎                                                                   | 5/11 [00:00<00:01,  4.73it/s]
+
 55%|███████████████████████████████████████████████████████████████████▋                                                        | 6/11 [00:01<00:01,  4.83it/s]
+
 64%|██████████████████████████████████████████████████████████████████████████████▉                                             | 7/11 [00:01<00:00,  4.77it/s]
+
 73%|██████████████████████████████████████████████████████████████████████████████████████████▏                                 | 8/11 [00:01<00:00,  4.73it/s]
+
 82%|█████████████████████████████████████████████████████████████████████████████████████████████████████▍                      | 9/11 [00:01<00:00,  4.44it/s]
+
 91%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████▊           | 10/11 [00:02<00:00,  4.61it/s]
+
                                                                                                                                                                
+
                                                                                                                                                                
+
 50%|█████████████████████████████████████████████████████████████▌                                                             | 20/40 [01:06<00:59,  2.98s/it]
+
+
                                                                                                                                                                
 52%|████████████████████████████████████████████████████████████████▌                                                          | 21/40 [01:07<00:57,  3.01s/it]
 55%|███████████████████████████████████████████████████████████████████▋                                                       | 22/40 [01:11<01:00,  3.38s/it]
 57%|██████████████████████████████████████████████████████████████████████▋                                                    | 23/40 [01:14<00:54,  3.20s/it]
 60%|█████████████████████████████████████████████████████████████████████████▊                                                 | 24/40 [01:15<00:39,  2.47s/it]
 62%|████████████████████████████████████████████████████████████████████████████▉                                              | 25/40 [01:19<00:45,  3.00s/it]
                                                                                                                                                                
+
 62%|████████████████████████████████████████████████████████████████████████████▉                                              | 25/40 [01:19<00:45,  3.00s/it][2025-11-25 02:22:48,145] [INFO] [axolotl.core.trainers.base.evaluate:376] [PID:3847] Running evaluation step...
+
+
  0%|                                                                                                                                    | 0/11 [00:00<?, ?it/s]
+
 18%|██████████████████████▌                                                                                                     | 2/11 [00:00<00:00,  9.37it/s]
+
 27%|█████████████████████████████████▊                                                                                          | 3/11 [00:00<00:01,  6.59it/s]
+
 36%|█████████████████████████████████████████████                                                                               | 4/11 [00:00<00:01,  5.70it/s]
+
 45%|████████████████████████████████████████████████████████▎                                                                   | 5/11 [00:00<00:01,  4.72it/s]
+
 55%|███████████████████████████████████████████████████████████████████▋                                                        | 6/11 [00:01<00:01,  4.82it/s]
+
 64%|██████████████████████████████████████████████████████████████████████████████▉                                             | 7/11 [00:01<00:00,  4.76it/s]
+
 73%|██████████████████████████████████████████████████████████████████████████████████████████▏                                 | 8/11 [00:01<00:00,  4.73it/s]
+
 82%|█████████████████████████████████████████████████████████████████████████████████████████████████████▍                      | 9/11 [00:01<00:00,  4.44it/s]
+
 91%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████▊           | 10/11 [00:02<00:00,  4.61it/s]
+
                                                                                                                                                                
+
                                                                                                                                                                
+
 62%|████████████████████████████████████████████████████████████████████████████▉                                              | 25/40 [01:21<00:45,  3.00s/it]
+
+
                                                                                                                                                                
 65%|███████████████████████████████████████████████████████████████████████████████▉                                           | 26/40 [01:24<00:52,  3.74s/it]
 68%|███████████████████████████████████████████████████████████████████████████████████                                        | 27/40 [01:25<00:35,  2.77s/it]
 70%|██████████████████████████████████████████████████████████████████████████████████████                                     | 28/40 [01:29<00:38,  3.24s/it]
 72%|█████████████████████████████████████████████████████████████████████████████████████████▏                                 | 29/40 [01:32<00:34,  3.10s/it]
 75%|████████████████████████████████████████████████████████████████████████████████████████████▎                              | 30/40 [01:33<00:23,  2.32s/it]
                                                                                                                                                                
+
 75%|████████████████████████████████████████████████████████████████████████████████████████████▎                              | 30/40 [01:33<00:23,  2.32s/it][2025-11-25 02:23:01,739] [INFO] [axolotl.core.trainers.base.evaluate:376] [PID:3847] Running evaluation step...
+
+
  0%|                                                                                                                                    | 0/11 [00:00<?, ?it/s]
+
 18%|██████████████████████▌                                                                                                     | 2/11 [00:00<00:00,  9.37it/s]
+
 27%|█████████████████████████████████▊                                                                                          | 3/11 [00:00<00:01,  6.58it/s]
+
 36%|█████████████████████████████████████████████                                                                               | 4/11 [00:00<00:01,  5.69it/s]
+
 45%|████████████████████████████████████████████████████████▎                                                                   | 5/11 [00:00<00:01,  4.75it/s]
+
 55%|███████████████████████████████████████████████████████████████████▋                                                        | 6/11 [00:01<00:01,  4.84it/s]
+
 64%|██████████████████████████████████████████████████████████████████████████████▉                                             | 7/11 [00:01<00:00,  4.78it/s]
+
 73%|██████████████████████████████████████████████████████████████████████████████████████████▏                                 | 8/11 [00:01<00:00,  4.74it/s]
+
 82%|█████████████████████████████████████████████████████████████████████████████████████████████████████▍                      | 9/11 [00:01<00:00,  4.42it/s]
+
 91%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████▊           | 10/11 [00:02<00:00,  4.61it/s]
+
                                                                                                                                                                
+
                                                                                                                                                                
+
 75%|████████████████████████████████████████████████████████████████████████████████████████████▎                              | 30/40 [01:35<00:23,  2.32s/it]
+
+
                                                                                                                                                                
 78%|███████████████████████████████████████████████████████████████████████████████████████████████▎                           | 31/40 [01:39<00:33,  3.68s/it]
 80%|██████████████████████████████████████████████████████████████████████████████████████████████████▍                        | 32/40 [01:42<00:27,  3.42s/it]
 82%|████████████████████████████████████████████���████████████████████████████████████████████████████████▍                     | 33/40 [01:43<00:17,  2.54s/it]
 85%|████████████████████████████████████████████████████████████████████████████████████████████████████████▌                  | 34/40 [01:47<00:18,  3.06s/it]
 88%|███████████████████████████████████████████████████████████████████████████████████████████████████████████▋               | 35/40 [01:50<00:14,  2.98s/it]
                                                                                                                                                                
+
 88%|███████████████████████████████████████████████████████████████████████████████████████████████████████████▋               | 35/40 [01:50<00:14,  2.98s/it][2025-11-25 02:23:18,936] [INFO] [axolotl.core.trainers.base.evaluate:376] [PID:3847] Running evaluation step...
+
+
  0%|                                                                                                                                    | 0/11 [00:00<?, ?it/s]
+
 18%|██████████████████████▌                                                                                                     | 2/11 [00:00<00:00,  9.34it/s]
+
 27%|█████████████████████████████████▊                                                                                          | 3/11 [00:00<00:01,  6.57it/s]
+
 36%|█████████████████████████████████████████████                                                                               | 4/11 [00:00<00:01,  5.70it/s]
+
 45%|████████████████████████████████████████████████████████▎                                                                   | 5/11 [00:00<00:01,  4.73it/s]
+
 55%|███████████████████████████████████████████████████████████████████▋                                                        | 6/11 [00:01<00:01,  4.84it/s]
+
 64%|██████████████████████████████████████████████████████████████████████████████▉                                             | 7/11 [00:01<00:00,  4.78it/s]
+
 73%|██████████████████████████████████████████████████████████████████████████████████████████▏                                 | 8/11 [00:01<00:00,  4.73it/s]
+
 82%|█████████████████████████████████████████████████████████████████████████████████████████████████████▍                      | 9/11 [00:01<00:00,  4.45it/s]
+
 91%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████▊           | 10/11 [00:02<00:00,  4.61it/s]
+
                                                                                                                                                                
+
                                                                                                                                                                
+
 88%|███████████████████████████████████████████████████████████████████████████████████████████████████████████▋               | 35/40 [01:52<00:14,  2.98s/it]
+
+
                                                                                                                                                                
 90%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████▋            | 36/40 [01:53<00:12,  3.01s/it]
 92%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████▊         | 37/40 [01:57<00:10,  3.38s/it]
 95%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▊      | 38/40 [02:00<00:06,  3.20s/it]
 98%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▉   | 39/40 [02:00<00:02,  2.39s/it]
                                                                                                                                                                
+
+
+
  0%|                                                                                                                                    | 0/11 [00:00<?, ?it/s]
+
 18%|██████████████████████▌                                                                                                     | 2/11 [00:00<00:00,  9.37it/s]
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 27%|█████████████████████████████████▊                                                                                          | 3/11 [00:00<00:01,  6.59it/s]
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 36%|█████████████████████████████████████████████                                                                               | 4/11 [00:00<00:01,  5.71it/s]
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 45%|████████████████████████████████████████████████████████▎                                                                   | 5/11 [00:00<00:01,  4.75it/s]
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 55%|███████████████████████████████████████████████████████████████████▋                                                        | 6/11 [00:01<00:01,  4.84it/s]
+
 64%|██████████████████████████████████████████████████████████████████████████████▉                                             | 7/11 [00:01<00:00,  4.78it/s]
+
 73%|██████████████████████████████████████████████████████████████████████████████████████████▏                                 | 8/11 [00:01<00:00,  4.74it/s]
+
 82%|█████████████████████████████████████████████████████████████████████████████████████████████████████▍                      | 9/11 [00:01<00:00,  4.45it/s]
+
 91%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████▊           | 10/11 [00:02<00:00,  4.62it/s]
+
                                                                                                                                                                
+
                                                                                                                                                                
+
+
+
                                                                                                                                                                [2025-11-25 02:23:36,386] [INFO] [axolotl.core.trainers.base._save:671] [PID:3847] Saving model checkpoint to ./outputs/astrid-llama-8b/checkpoint-40
+
                                                                                                                                                                
+
+[2025-11-25 02:24:50,146] [INFO] [axolotl.train.save_trained_model:218] [PID:3847] Training completed! Saving trained model to ./outputs/astrid-llama-8b.
+[2025-11-25 02:24:52,766] [INFO] [axolotl.train.save_trained_model:336] [PID:3847] Model successfully saved to ./outputs/astrid-llama-8b

special_tokens_map.json

@@ -0,0 +1,23 @@
+{
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+    "content": "<|begin_of_text|>",
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tokenizer.json

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+oid sha256:6b9e4e7fb171f92fd137b777cc2714bf87d11576700a1dcd7a399e7bbe39537b
+size 17209920

tokenizer_config.json

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