Upload folder using huggingface_hub

README.md

@@ -0,0 +1,207 @@
+---
+base_model: mistralai/Mistral-7B-Instruct-v0.3
+library_name: peft
+pipeline_tag: text-generation
+tags:
+- base_model:adapter:mistralai/Mistral-7B-Instruct-v0.3
+- 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

adapter_config.json

@@ -0,0 +1,37 @@
+{
+  "alpha_pattern": {},
+  "auto_mapping": null,
+  "base_model_name_or_path": "mistralai/Mistral-7B-Instruct-v0.3",
+  "bias": "none",
+  "corda_config": null,
+  "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": 0.05,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "qalora_group_size": 16,
+  "r": 16,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "q_proj",
+    "v_proj"
+  ],
+  "target_parameters": null,
+  "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 sha256:7310bd5cdac0e96e60625be9080e2baa5ada4d62d6ae6bef9bf8c141c8b4bd9b
+size 27280152

chat_template.jinja

@@ -0,0 +1,87 @@
+{%- if messages[0]["role"] == "system" %}
+    {%- set system_message = messages[0]["content"] %}
+    {%- set loop_messages = messages[1:] %}
+{%- else %}
+    {%- set loop_messages = messages %}
+{%- endif %}
+{%- if not tools is defined %}
+    {%- set tools = none %}
+{%- endif %}
+{%- set user_messages = loop_messages | selectattr("role", "equalto", "user") | list %}
+
+{#- This block checks for alternating user/assistant messages, skipping tool calling messages #}
+{%- set ns = namespace() %}
+{%- set ns.index = 0 %}
+{%- for message in loop_messages %}
+    {%- if not (message.role == "tool" or message.role == "tool_results" or (message.tool_calls is defined and message.tool_calls is not none)) %}
+        {%- if (message["role"] == "user") != (ns.index % 2 == 0) %}
+            {{- raise_exception("After the optional system message, conversation roles must alternate user/assistant/user/assistant/...") }}
+        {%- endif %}
+        {%- set ns.index = ns.index + 1 %}
+    {%- endif %}
+{%- endfor %}
+
+{{- bos_token }}
+{%- for message in loop_messages %}
+    {%- if message["role"] == "user" %}
+        {%- if tools is not none and (message == user_messages[-1]) %}
+            {{- "[AVAILABLE_TOOLS] [" }}
+            {%- for tool in tools %}
+                {%- set tool = tool.function %}
+                {{- '{"type": "function", "function": {' }}
+                {%- for key, val in tool.items() if key != "return" %}
+                    {%- if val is string %}
+                        {{- '"' + key + '": "' + val + '"' }}
+                    {%- else %}
+                        {{- '"' + key + '": ' + val|tojson }}
+                    {%- endif %}
+                    {%- if not loop.last %}
+                        {{- ", " }}
+                    {%- endif %}
+                {%- endfor %}
+                {{- "}}" }}
+                {%- if not loop.last %}
+                    {{- ", " }}
+                {%- else %}
+                    {{- "]" }}
+                {%- endif %}
+            {%- endfor %}
+            {{- "[/AVAILABLE_TOOLS]" }}
+            {%- endif %}
+        {%- if loop.last and system_message is defined %}
+            {{- "[INST] " + system_message + "\n\n" + message["content"] + "[/INST]" }}
+        {%- else %}
+            {{- "[INST] " + message["content"] + "[/INST]" }}
+        {%- endif %}
+    {%- elif message.tool_calls is defined and message.tool_calls is not none %}
+        {{- "[TOOL_CALLS] [" }}
+        {%- for tool_call in message.tool_calls %}
+            {%- set out = tool_call.function|tojson %}
+            {{- out[:-1] }}
+            {%- if not tool_call.id is defined or tool_call.id|length != 9 %}
+                {{- raise_exception("Tool call IDs should be alphanumeric strings with length 9!") }}
+            {%- endif %}
+            {{- ', "id": "' + tool_call.id + '"}' }}
+            {%- if not loop.last %}
+                {{- ", " }}
+            {%- else %}
+                {{- "]" + eos_token }}
+            {%- endif %}
+        {%- endfor %}
+    {%- elif message["role"] == "assistant" %}
+        {{- " " + message["content"]|trim + eos_token}}
+    {%- elif message["role"] == "tool_results" or message["role"] == "tool" %}
+        {%- if message.content is defined and message.content.content is defined %}
+            {%- set content = message.content.content %}
+        {%- else %}
+            {%- set content = message.content %}
+        {%- endif %}
+        {{- '[TOOL_RESULTS] {"content": ' + content|string + ", " }}
+        {%- if not message.tool_call_id is defined or message.tool_call_id|length != 9 %}
+            {{- raise_exception("Tool call IDs should be alphanumeric strings with length 9!") }}
+        {%- endif %}
+        {{- '"call_id": "' + message.tool_call_id + '"}[/TOOL_RESULTS]' }}
+    {%- else %}
+        {{- raise_exception("Only user and assistant roles are supported, with the exception of an initial optional system message!") }}
+    {%- endif %}
+{%- endfor %}

checkpoint-410/README.md

@@ -0,0 +1,207 @@
+---
+base_model: mistralai/Mistral-7B-Instruct-v0.3
+library_name: peft
+pipeline_tag: text-generation
+tags:
+- base_model:adapter:mistralai/Mistral-7B-Instruct-v0.3
+- 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-410/adapter_config.json

@@ -0,0 +1,37 @@
+{
+  "alpha_pattern": {},
+  "auto_mapping": null,
+  "base_model_name_or_path": "mistralai/Mistral-7B-Instruct-v0.3",
+  "bias": "none",
+  "corda_config": null,
+  "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": 0.05,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "qalora_group_size": 16,
+  "r": 16,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "q_proj",
+    "v_proj"
+  ],
+  "target_parameters": null,
+  "task_type": "CAUSAL_LM",
+  "trainable_token_indices": null,
+  "use_dora": false,
+  "use_qalora": false,
+  "use_rslora": false
+}

checkpoint-410/adapter_model.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:b20fae71d882abdd0bc9477fae2045b407904c9ea15ea877f0c9993cf9fa3fed
+size 27280152

checkpoint-410/optimizer.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:498a67e77de1222aaba1ba471224cef172b7cffc898f013f57e79d6b96d98d23
+size 54636235

checkpoint-410/rng_state.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:22aef3df2367ea7da8b6ce1f68b5241aa8aac5ec108641dd3326b6ac59ebb1c2
+size 14645

checkpoint-410/scaler.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:ac6ad17c6a8c86030146e63684fda11ce325d6fb30293c0d06ad21be0385527f
+size 1383

checkpoint-410/scheduler.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:bfbb8fed946bbe258a94cb211e3043bbffc159e04e541ba942b2b891dcbc9eb7
+size 1465

checkpoint-410/trainer_state.json

@@ -0,0 +1,337 @@
+{
+  "best_global_step": null,
+  "best_metric": null,
+  "best_model_checkpoint": null,
+  "epoch": 2.0,
+  "eval_steps": 500,
+  "global_step": 410,
+  "is_hyper_param_search": false,
+  "is_local_process_zero": true,
+  "is_world_process_zero": true,
+  "log_history": [
+    {
+      "epoch": 0.04884004884004884,
+      "grad_norm": 0.6565904021263123,
+      "learning_rate": 0.00018,
+      "loss": 2.306,
+      "step": 10
+    },
+    {
+      "epoch": 0.09768009768009768,
+      "grad_norm": 0.4782625734806061,
+      "learning_rate": 0.00019702479338842976,
+      "loss": 1.8776,
+      "step": 20
+    },
+    {
+      "epoch": 0.14652014652014653,
+      "grad_norm": 0.34842449426651,
+      "learning_rate": 0.0001937190082644628,
+      "loss": 1.986,
+      "step": 30
+    },
+    {
+      "epoch": 0.19536019536019536,
+      "grad_norm": 0.5142027735710144,
+      "learning_rate": 0.0001904132231404959,
+      "loss": 1.953,
+      "step": 40
+    },
+    {
+      "epoch": 0.2442002442002442,
+      "grad_norm": 0.4530898332595825,
+      "learning_rate": 0.00018710743801652891,
+      "loss": 1.8595,
+      "step": 50
+    },
+    {
+      "epoch": 0.29304029304029305,
+      "grad_norm": 0.4601179361343384,
+      "learning_rate": 0.000183801652892562,
+      "loss": 1.9006,
+      "step": 60
+    },
+    {
+      "epoch": 0.3418803418803419,
+      "grad_norm": 0.49045854806900024,
+      "learning_rate": 0.00018049586776859504,
+      "loss": 1.6583,
+      "step": 70
+    },
+    {
+      "epoch": 0.3907203907203907,
+      "grad_norm": 0.4943140745162964,
+      "learning_rate": 0.0001771900826446281,
+      "loss": 1.841,
+      "step": 80
+    },
+    {
+      "epoch": 0.43956043956043955,
+      "grad_norm": 0.43958303332328796,
+      "learning_rate": 0.00017388429752066115,
+      "loss": 1.7377,
+      "step": 90
+    },
+    {
+      "epoch": 0.4884004884004884,
+      "grad_norm": 0.4475325047969818,
+      "learning_rate": 0.00017057851239669423,
+      "loss": 1.9054,
+      "step": 100
+    },
+    {
+      "epoch": 0.5372405372405372,
+      "grad_norm": 0.4703655242919922,
+      "learning_rate": 0.00016727272727272728,
+      "loss": 1.7999,
+      "step": 110
+    },
+    {
+      "epoch": 0.5860805860805861,
+      "grad_norm": 0.47283482551574707,
+      "learning_rate": 0.00016396694214876033,
+      "loss": 1.8296,
+      "step": 120
+    },
+    {
+      "epoch": 0.6349206349206349,
+      "grad_norm": 0.45280855894088745,
+      "learning_rate": 0.00016066115702479338,
+      "loss": 1.6442,
+      "step": 130
+    },
+    {
+      "epoch": 0.6837606837606838,
+      "grad_norm": 0.4415304362773895,
+      "learning_rate": 0.00015735537190082646,
+      "loss": 1.8178,
+      "step": 140
+    },
+    {
+      "epoch": 0.7326007326007326,
+      "grad_norm": 0.6615126729011536,
+      "learning_rate": 0.0001540495867768595,
+      "loss": 1.9372,
+      "step": 150
+    },
+    {
+      "epoch": 0.7814407814407814,
+      "grad_norm": 0.5677676200866699,
+      "learning_rate": 0.00015074380165289256,
+      "loss": 1.6327,
+      "step": 160
+    },
+    {
+      "epoch": 0.8302808302808303,
+      "grad_norm": 0.528029203414917,
+      "learning_rate": 0.00014743801652892564,
+      "loss": 1.7825,
+      "step": 170
+    },
+    {
+      "epoch": 0.8791208791208791,
+      "grad_norm": 0.6582658290863037,
+      "learning_rate": 0.0001441322314049587,
+      "loss": 1.9638,
+      "step": 180
+    },
+    {
+      "epoch": 0.927960927960928,
+      "grad_norm": 0.6919686198234558,
+      "learning_rate": 0.00014082644628099175,
+      "loss": 1.8914,
+      "step": 190
+    },
+    {
+      "epoch": 0.9768009768009768,
+      "grad_norm": 0.3584222197532654,
+      "learning_rate": 0.0001375206611570248,
+      "loss": 1.7909,
+      "step": 200
+    },
+    {
+      "epoch": 1.0,
+      "eval_loss": 1.735278844833374,
+      "eval_runtime": 19.9432,
+      "eval_samples_per_second": 9.126,
+      "eval_steps_per_second": 1.153,
+      "step": 205
+    },
+    {
+      "epoch": 1.0244200244200243,
+      "grad_norm": 0.6349706649780273,
+      "learning_rate": 0.00013421487603305788,
+      "loss": 1.8237,
+      "step": 210
+    },
+    {
+      "epoch": 1.0732600732600732,
+      "grad_norm": 0.338216632604599,
+      "learning_rate": 0.00013090909090909093,
+      "loss": 1.7347,
+      "step": 220
+    },
+    {
+      "epoch": 1.122100122100122,
+      "grad_norm": 0.43673205375671387,
+      "learning_rate": 0.00012760330578512398,
+      "loss": 1.6828,
+      "step": 230
+    },
+    {
+      "epoch": 1.170940170940171,
+      "grad_norm": 0.3703135550022125,
+      "learning_rate": 0.00012429752066115703,
+      "loss": 1.6821,
+      "step": 240
+    },
+    {
+      "epoch": 1.2197802197802199,
+      "grad_norm": 0.4435603618621826,
+      "learning_rate": 0.0001209917355371901,
+      "loss": 1.7656,
+      "step": 250
+    },
+    {
+      "epoch": 1.2686202686202686,
+      "grad_norm": 0.5340843200683594,
+      "learning_rate": 0.00011768595041322315,
+      "loss": 1.792,
+      "step": 260
+    },
+    {
+      "epoch": 1.3174603174603174,
+      "grad_norm": 0.37987396121025085,
+      "learning_rate": 0.00011438016528925621,
+      "loss": 1.7761,
+      "step": 270
+    },
+    {
+      "epoch": 1.3663003663003663,
+      "grad_norm": 0.33273303508758545,
+      "learning_rate": 0.00011107438016528926,
+      "loss": 1.6398,
+      "step": 280
+    },
+    {
+      "epoch": 1.4151404151404152,
+      "grad_norm": 0.4231277406215668,
+      "learning_rate": 0.00010776859504132233,
+      "loss": 1.8901,
+      "step": 290
+    },
+    {
+      "epoch": 1.463980463980464,
+      "grad_norm": 0.2134978324174881,
+      "learning_rate": 0.00010446280991735538,
+      "loss": 1.8604,
+      "step": 300
+    },
+    {
+      "epoch": 1.5128205128205128,
+      "grad_norm": 0.43554314970970154,
+      "learning_rate": 0.00010115702479338845,
+      "loss": 1.7911,
+      "step": 310
+    },
+    {
+      "epoch": 1.5616605616605617,
+      "grad_norm": 0.20964309573173523,
+      "learning_rate": 9.785123966942148e-05,
+      "loss": 1.6337,
+      "step": 320
+    },
+    {
+      "epoch": 1.6105006105006106,
+      "grad_norm": 0.5670686364173889,
+      "learning_rate": 9.454545454545455e-05,
+      "loss": 1.7667,
+      "step": 330
+    },
+    {
+      "epoch": 1.6593406593406592,
+      "grad_norm": 0.28007999062538147,
+      "learning_rate": 9.12396694214876e-05,
+      "loss": 1.7941,
+      "step": 340
+    },
+    {
+      "epoch": 1.7081807081807083,
+      "grad_norm": 0.244796484708786,
+      "learning_rate": 8.793388429752067e-05,
+      "loss": 1.6848,
+      "step": 350
+    },
+    {
+      "epoch": 1.757020757020757,
+      "grad_norm": 0.2684899866580963,
+      "learning_rate": 8.462809917355372e-05,
+      "loss": 1.8238,
+      "step": 360
+    },
+    {
+      "epoch": 1.8058608058608059,
+      "grad_norm": 0.2789863049983978,
+      "learning_rate": 8.132231404958678e-05,
+      "loss": 1.7551,
+      "step": 370
+    },
+    {
+      "epoch": 1.8547008547008548,
+      "grad_norm": 0.2315087765455246,
+      "learning_rate": 7.801652892561983e-05,
+      "loss": 1.6725,
+      "step": 380
+    },
+    {
+      "epoch": 1.9035409035409034,
+      "grad_norm": 0.2351648360490799,
+      "learning_rate": 7.47107438016529e-05,
+      "loss": 1.7861,
+      "step": 390
+    },
+    {
+      "epoch": 1.9523809523809523,
+      "grad_norm": 0.15907102823257446,
+      "learning_rate": 7.140495867768595e-05,
+      "loss": 1.6753,
+      "step": 400
+    },
+    {
+      "epoch": 2.0,
+      "grad_norm": 0.15325959026813507,
+      "learning_rate": 6.8099173553719e-05,
+      "loss": 1.8352,
+      "step": 410
+    },
+    {
+      "epoch": 2.0,
+      "eval_loss": 1.7097043991088867,
+      "eval_runtime": 19.9498,
+      "eval_samples_per_second": 9.123,
+      "eval_steps_per_second": 1.153,
+      "step": 410
+    }
+  ],
+  "logging_steps": 10,
+  "max_steps": 615,
+  "num_input_tokens_seen": 0,
+  "num_train_epochs": 3,
+  "save_steps": 500,
+  "stateful_callbacks": {
+    "TrainerControl": {
+      "args": {
+        "should_epoch_stop": false,
+        "should_evaluate": false,
+        "should_log": false,
+        "should_save": true,
+        "should_training_stop": false
+      },
+      "attributes": {}
+    }
+  },
+  "total_flos": 1.433220480415826e+17,
+  "train_batch_size": 1,
+  "trial_name": null,
+  "trial_params": null
+}

checkpoint-410/training_args.bin

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:d91f4cbf3cd0a6d6f917302881f00ad5f5a4b3059dba94b59bdffe68e30afaf4
+size 5905

checkpoint-615/README.md

@@ -0,0 +1,207 @@
+---
+base_model: mistralai/Mistral-7B-Instruct-v0.3
+library_name: peft
+pipeline_tag: text-generation
+tags:
+- base_model:adapter:mistralai/Mistral-7B-Instruct-v0.3
+- 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-615/adapter_config.json

@@ -0,0 +1,37 @@
+{
+  "alpha_pattern": {},
+  "auto_mapping": null,
+  "base_model_name_or_path": "mistralai/Mistral-7B-Instruct-v0.3",
+  "bias": "none",
+  "corda_config": null,
+  "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": 0.05,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "qalora_group_size": 16,
+  "r": 16,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "q_proj",
+    "v_proj"
+  ],
+  "target_parameters": null,
+  "task_type": "CAUSAL_LM",
+  "trainable_token_indices": null,
+  "use_dora": false,
+  "use_qalora": false,
+  "use_rslora": false
+}

checkpoint-615/adapter_model.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:7310bd5cdac0e96e60625be9080e2baa5ada4d62d6ae6bef9bf8c141c8b4bd9b
+size 27280152

checkpoint-615/optimizer.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:8ff5c5bc4841f55e65637c58c0b084258cf4205c0b89f4cf5971d21e695c4732
+size 54636235

checkpoint-615/rng_state.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:8ac677aedd334f823cefc9c1ef31c987d08d2e1867b02203efc778847d1a2949
+size 14645

checkpoint-615/scaler.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:59bf985af78a95922eb89c5db9a7d99258c9c2d800308c27d8ef439640af7446
+size 1383

checkpoint-615/scheduler.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:4f9c8067aa1464f74c5bf63bc7dd6be3931d3294bdb2f3fc41f12c01477dd25b
+size 1465

checkpoint-615/trainer_state.json

@@ -0,0 +1,485 @@
+{
+  "best_global_step": null,
+  "best_metric": null,
+  "best_model_checkpoint": null,
+  "epoch": 3.0,
+  "eval_steps": 500,
+  "global_step": 615,
+  "is_hyper_param_search": false,
+  "is_local_process_zero": true,
+  "is_world_process_zero": true,
+  "log_history": [
+    {
+      "epoch": 0.04884004884004884,
+      "grad_norm": 0.6565904021263123,
+      "learning_rate": 0.00018,
+      "loss": 2.306,
+      "step": 10
+    },
+    {
+      "epoch": 0.09768009768009768,
+      "grad_norm": 0.4782625734806061,
+      "learning_rate": 0.00019702479338842976,
+      "loss": 1.8776,
+      "step": 20
+    },
+    {
+      "epoch": 0.14652014652014653,
+      "grad_norm": 0.34842449426651,
+      "learning_rate": 0.0001937190082644628,
+      "loss": 1.986,
+      "step": 30
+    },
+    {
+      "epoch": 0.19536019536019536,
+      "grad_norm": 0.5142027735710144,
+      "learning_rate": 0.0001904132231404959,
+      "loss": 1.953,
+      "step": 40
+    },
+    {
+      "epoch": 0.2442002442002442,
+      "grad_norm": 0.4530898332595825,
+      "learning_rate": 0.00018710743801652891,
+      "loss": 1.8595,
+      "step": 50
+    },
+    {
+      "epoch": 0.29304029304029305,
+      "grad_norm": 0.4601179361343384,
+      "learning_rate": 0.000183801652892562,
+      "loss": 1.9006,
+      "step": 60
+    },
+    {
+      "epoch": 0.3418803418803419,
+      "grad_norm": 0.49045854806900024,
+      "learning_rate": 0.00018049586776859504,
+      "loss": 1.6583,
+      "step": 70
+    },
+    {
+      "epoch": 0.3907203907203907,
+      "grad_norm": 0.4943140745162964,
+      "learning_rate": 0.0001771900826446281,
+      "loss": 1.841,
+      "step": 80
+    },
+    {
+      "epoch": 0.43956043956043955,
+      "grad_norm": 0.43958303332328796,
+      "learning_rate": 0.00017388429752066115,
+      "loss": 1.7377,
+      "step": 90
+    },
+    {
+      "epoch": 0.4884004884004884,
+      "grad_norm": 0.4475325047969818,
+      "learning_rate": 0.00017057851239669423,
+      "loss": 1.9054,
+      "step": 100
+    },
+    {
+      "epoch": 0.5372405372405372,
+      "grad_norm": 0.4703655242919922,
+      "learning_rate": 0.00016727272727272728,
+      "loss": 1.7999,
+      "step": 110
+    },
+    {
+      "epoch": 0.5860805860805861,
+      "grad_norm": 0.47283482551574707,
+      "learning_rate": 0.00016396694214876033,
+      "loss": 1.8296,
+      "step": 120
+    },
+    {
+      "epoch": 0.6349206349206349,
+      "grad_norm": 0.45280855894088745,
+      "learning_rate": 0.00016066115702479338,
+      "loss": 1.6442,
+      "step": 130
+    },
+    {
+      "epoch": 0.6837606837606838,
+      "grad_norm": 0.4415304362773895,
+      "learning_rate": 0.00015735537190082646,
+      "loss": 1.8178,
+      "step": 140
+    },
+    {
+      "epoch": 0.7326007326007326,
+      "grad_norm": 0.6615126729011536,
+      "learning_rate": 0.0001540495867768595,
+      "loss": 1.9372,
+      "step": 150
+    },
+    {
+      "epoch": 0.7814407814407814,
+      "grad_norm": 0.5677676200866699,
+      "learning_rate": 0.00015074380165289256,
+      "loss": 1.6327,
+      "step": 160
+    },
+    {
+      "epoch": 0.8302808302808303,
+      "grad_norm": 0.528029203414917,
+      "learning_rate": 0.00014743801652892564,
+      "loss": 1.7825,
+      "step": 170
+    },
+    {
+      "epoch": 0.8791208791208791,
+      "grad_norm": 0.6582658290863037,
+      "learning_rate": 0.0001441322314049587,
+      "loss": 1.9638,
+      "step": 180
+    },
+    {
+      "epoch": 0.927960927960928,
+      "grad_norm": 0.6919686198234558,
+      "learning_rate": 0.00014082644628099175,
+      "loss": 1.8914,
+      "step": 190
+    },
+    {
+      "epoch": 0.9768009768009768,
+      "grad_norm": 0.3584222197532654,
+      "learning_rate": 0.0001375206611570248,
+      "loss": 1.7909,
+      "step": 200
+    },
+    {
+      "epoch": 1.0,
+      "eval_loss": 1.735278844833374,
+      "eval_runtime": 19.9432,
+      "eval_samples_per_second": 9.126,
+      "eval_steps_per_second": 1.153,
+      "step": 205
+    },
+    {
+      "epoch": 1.0244200244200243,
+      "grad_norm": 0.6349706649780273,
+      "learning_rate": 0.00013421487603305788,
+      "loss": 1.8237,
+      "step": 210
+    },
+    {
+      "epoch": 1.0732600732600732,
+      "grad_norm": 0.338216632604599,
+      "learning_rate": 0.00013090909090909093,
+      "loss": 1.7347,
+      "step": 220
+    },
+    {
+      "epoch": 1.122100122100122,
+      "grad_norm": 0.43673205375671387,
+      "learning_rate": 0.00012760330578512398,
+      "loss": 1.6828,
+      "step": 230
+    },
+    {
+      "epoch": 1.170940170940171,
+      "grad_norm": 0.3703135550022125,
+      "learning_rate": 0.00012429752066115703,
+      "loss": 1.6821,
+      "step": 240
+    },
+    {
+      "epoch": 1.2197802197802199,
+      "grad_norm": 0.4435603618621826,
+      "learning_rate": 0.0001209917355371901,
+      "loss": 1.7656,
+      "step": 250
+    },
+    {
+      "epoch": 1.2686202686202686,
+      "grad_norm": 0.5340843200683594,
+      "learning_rate": 0.00011768595041322315,
+      "loss": 1.792,
+      "step": 260
+    },
+    {
+      "epoch": 1.3174603174603174,
+      "grad_norm": 0.37987396121025085,
+      "learning_rate": 0.00011438016528925621,
+      "loss": 1.7761,
+      "step": 270
+    },
+    {
+      "epoch": 1.3663003663003663,
+      "grad_norm": 0.33273303508758545,
+      "learning_rate": 0.00011107438016528926,
+      "loss": 1.6398,
+      "step": 280
+    },
+    {
+      "epoch": 1.4151404151404152,
+      "grad_norm": 0.4231277406215668,
+      "learning_rate": 0.00010776859504132233,
+      "loss": 1.8901,
+      "step": 290
+    },
+    {
+      "epoch": 1.463980463980464,
+      "grad_norm": 0.2134978324174881,
+      "learning_rate": 0.00010446280991735538,
+      "loss": 1.8604,
+      "step": 300
+    },
+    {
+      "epoch": 1.5128205128205128,
+      "grad_norm": 0.43554314970970154,
+      "learning_rate": 0.00010115702479338845,
+      "loss": 1.7911,
+      "step": 310
+    },
+    {
+      "epoch": 1.5616605616605617,
+      "grad_norm": 0.20964309573173523,
+      "learning_rate": 9.785123966942148e-05,
+      "loss": 1.6337,
+      "step": 320
+    },
+    {
+      "epoch": 1.6105006105006106,
+      "grad_norm": 0.5670686364173889,
+      "learning_rate": 9.454545454545455e-05,
+      "loss": 1.7667,
+      "step": 330
+    },
+    {
+      "epoch": 1.6593406593406592,
+      "grad_norm": 0.28007999062538147,
+      "learning_rate": 9.12396694214876e-05,
+      "loss": 1.7941,
+      "step": 340
+    },
+    {
+      "epoch": 1.7081807081807083,
+      "grad_norm": 0.244796484708786,
+      "learning_rate": 8.793388429752067e-05,
+      "loss": 1.6848,
+      "step": 350
+    },
+    {
+      "epoch": 1.757020757020757,
+      "grad_norm": 0.2684899866580963,
+      "learning_rate": 8.462809917355372e-05,
+      "loss": 1.8238,
+      "step": 360
+    },
+    {
+      "epoch": 1.8058608058608059,
+      "grad_norm": 0.2789863049983978,
+      "learning_rate": 8.132231404958678e-05,
+      "loss": 1.7551,
+      "step": 370
+    },
+    {
+      "epoch": 1.8547008547008548,
+      "grad_norm": 0.2315087765455246,
+      "learning_rate": 7.801652892561983e-05,
+      "loss": 1.6725,
+      "step": 380
+    },
+    {
+      "epoch": 1.9035409035409034,
+      "grad_norm": 0.2351648360490799,
+      "learning_rate": 7.47107438016529e-05,
+      "loss": 1.7861,
+      "step": 390
+    },
+    {
+      "epoch": 1.9523809523809523,
+      "grad_norm": 0.15907102823257446,
+      "learning_rate": 7.140495867768595e-05,
+      "loss": 1.6753,
+      "step": 400
+    },
+    {
+      "epoch": 2.0,
+      "grad_norm": 0.15325959026813507,
+      "learning_rate": 6.8099173553719e-05,
+      "loss": 1.8352,
+      "step": 410
+    },
+    {
+      "epoch": 2.0,
+      "eval_loss": 1.7097043991088867,
+      "eval_runtime": 19.9498,
+      "eval_samples_per_second": 9.123,
+      "eval_steps_per_second": 1.153,
+      "step": 410
+    },
+    {
+      "epoch": 2.0488400488400487,
+      "grad_norm": 0.10827562212944031,
+      "learning_rate": 6.479338842975207e-05,
+      "loss": 1.7363,
+      "step": 420
+    },
+    {
+      "epoch": 2.0976800976800978,
+      "grad_norm": 0.1293765902519226,
+      "learning_rate": 6.148760330578512e-05,
+      "loss": 1.726,
+      "step": 430
+    },
+    {
+      "epoch": 2.1465201465201464,
+      "grad_norm": 0.1775052547454834,
+      "learning_rate": 5.818181818181818e-05,
+      "loss": 1.6641,
+      "step": 440
+    },
+    {
+      "epoch": 2.1953601953601956,
+      "grad_norm": 0.10628961026668549,
+      "learning_rate": 5.487603305785124e-05,
+      "loss": 1.8193,
+      "step": 450
+    },
+    {
+      "epoch": 2.244200244200244,
+      "grad_norm": 0.11912493407726288,
+      "learning_rate": 5.1570247933884295e-05,
+      "loss": 1.6497,
+      "step": 460
+    },
+    {
+      "epoch": 2.293040293040293,
+      "grad_norm": 0.17353476583957672,
+      "learning_rate": 4.826446280991736e-05,
+      "loss": 1.7043,
+      "step": 470
+    },
+    {
+      "epoch": 2.341880341880342,
+      "grad_norm": 0.11081728339195251,
+      "learning_rate": 4.495867768595042e-05,
+      "loss": 1.7964,
+      "step": 480
+    },
+    {
+      "epoch": 2.3907203907203907,
+      "grad_norm": 0.09711920469999313,
+      "learning_rate": 4.165289256198348e-05,
+      "loss": 1.8315,
+      "step": 490
+    },
+    {
+      "epoch": 2.4395604395604398,
+      "grad_norm": 0.1099553108215332,
+      "learning_rate": 3.8347107438016536e-05,
+      "loss": 1.7696,
+      "step": 500
+    },
+    {
+      "epoch": 2.4884004884004884,
+      "grad_norm": 0.12278404831886292,
+      "learning_rate": 3.504132231404959e-05,
+      "loss": 1.7851,
+      "step": 510
+    },
+    {
+      "epoch": 2.537240537240537,
+      "grad_norm": 0.08975676447153091,
+      "learning_rate": 3.1735537190082646e-05,
+      "loss": 1.9197,
+      "step": 520
+    },
+    {
+      "epoch": 2.586080586080586,
+      "grad_norm": 0.08411797136068344,
+      "learning_rate": 2.8429752066115704e-05,
+      "loss": 1.6497,
+      "step": 530
+    },
+    {
+      "epoch": 2.634920634920635,
+      "grad_norm": 0.10348548740148544,
+      "learning_rate": 2.5123966942148763e-05,
+      "loss": 1.5763,
+      "step": 540
+    },
+    {
+      "epoch": 2.683760683760684,
+      "grad_norm": 0.10242890566587448,
+      "learning_rate": 2.1818181818181818e-05,
+      "loss": 1.5551,
+      "step": 550
+    },
+    {
+      "epoch": 2.7326007326007327,
+      "grad_norm": 0.09305644780397415,
+      "learning_rate": 1.8512396694214876e-05,
+      "loss": 1.8751,
+      "step": 560
+    },
+    {
+      "epoch": 2.7814407814407813,
+      "grad_norm": 0.10115351527929306,
+      "learning_rate": 1.5206611570247933e-05,
+      "loss": 1.6887,
+      "step": 570
+    },
+    {
+      "epoch": 2.8302808302808304,
+      "grad_norm": 0.0991702601313591,
+      "learning_rate": 1.1900826446280993e-05,
+      "loss": 1.6846,
+      "step": 580
+    },
+    {
+      "epoch": 2.879120879120879,
+      "grad_norm": 0.11022075265645981,
+      "learning_rate": 8.59504132231405e-06,
+      "loss": 1.88,
+      "step": 590
+    },
+    {
+      "epoch": 2.927960927960928,
+      "grad_norm": 0.12525387108325958,
+      "learning_rate": 5.289256198347107e-06,
+      "loss": 1.7041,
+      "step": 600
+    },
+    {
+      "epoch": 2.976800976800977,
+      "grad_norm": 0.1043957769870758,
+      "learning_rate": 1.9834710743801654e-06,
+      "loss": 1.8158,
+      "step": 610
+    },
+    {
+      "epoch": 3.0,
+      "eval_loss": 1.7082070112228394,
+      "eval_runtime": 19.9486,
+      "eval_samples_per_second": 9.123,
+      "eval_steps_per_second": 1.153,
+      "step": 615
+    }
+  ],
+  "logging_steps": 10,
+  "max_steps": 615,
+  "num_input_tokens_seen": 0,
+  "num_train_epochs": 3,
+  "save_steps": 500,
+  "stateful_callbacks": {
+    "TrainerControl": {
+      "args": {
+        "should_epoch_stop": false,
+        "should_evaluate": false,
+        "should_log": false,
+        "should_save": true,
+        "should_training_stop": true
+      },
+      "attributes": {}
+    }
+  },
+  "total_flos": 2.149830720623739e+17,
+  "train_batch_size": 1,
+  "trial_name": null,
+  "trial_params": null
+}

checkpoint-615/training_args.bin

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:d91f4cbf3cd0a6d6f917302881f00ad5f5a4b3059dba94b59bdffe68e30afaf4
+size 5905

runs/Oct29_18-28-07_299803b437f5/events.out.tfevents.1761762498.299803b437f5.1532.0

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:307acfa7fcbdcb72d62fe162d74dc71a565d2d3f17b839d808e6cf1b5382668a
+size 19545

special_tokens_map.json

@@ -0,0 +1,24 @@
+{
+  "bos_token": {
+    "content": "<s>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "eos_token": {
+    "content": "</s>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "pad_token": "</s>",
+  "unk_token": {
+    "content": "<unk>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  }
+}

tokenizer.model

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:37f00374dea48658ee8f5d0f21895b9bc55cb0103939607c8185bfd1c6ca1f89
+size 587404