Add files using upload-large-folder tool

.gitattributes

@@ -41,3 +41,5 @@ checkpoint-60/tokenizer.json filter=lfs diff=lfs merge=lfs -text
 checkpoint-120/tokenizer.json filter=lfs diff=lfs merge=lfs -text
 checkpoint-240/tokenizer.json filter=lfs diff=lfs merge=lfs -text
 checkpoint-180/tokenizer.json filter=lfs diff=lfs merge=lfs -text
+checkpoint-540/tokenizer.json filter=lfs diff=lfs merge=lfs -text
+checkpoint-600/tokenizer.json filter=lfs diff=lfs merge=lfs -text

checkpoint-540/README.md

@@ -0,0 +1,202 @@
+---
+base_model: Qwen/Qwen2.5-Coder-7B-Instruct
+library_name: peft
+---
+
+# 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 0.12.0

checkpoint-540/adapter_config.json

@@ -0,0 +1,34 @@
+{
+  "alpha_pattern": {},
+  "auto_mapping": null,
+  "base_model_name_or_path": "Qwen/Qwen2.5-Coder-7B-Instruct",
+  "bias": "none",
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layer_replication": null,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
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+  "lora_dropout": 0.1,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "r": 16,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
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+    "k_proj",
+    "v_proj",
+    "q_proj",
+    "o_proj",
+    "gate_proj",
+    "up_proj"
+  ],
+  "task_type": "CAUSAL_LM",
+  "use_dora": false,
+  "use_rslora": false
+}

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checkpoint-540/added_tokens.json

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+  "<|vision_pad|>": 151654,
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+}

checkpoint-540/optimizer.pt

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checkpoint-540/rng_state_0.pth

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checkpoint-540/rng_state_1.pth

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checkpoint-540/scheduler.pt

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checkpoint-540/special_tokens_map.json

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+{
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+  }
+}

checkpoint-540/tokenizer.json

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checkpoint-540/tokenizer_config.json

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+  "chat_template": "{%- if tools %}\n    {{- '<|im_start|>system\\n' }}\n    {%- if messages[0]['role'] == 'system' %}\n        {{- messages[0]['content'] }}\n    {%- else %}\n        {{- 'You are Qwen, created by Alibaba Cloud. You are a helpful assistant.' }}\n    {%- endif %}\n    {{- \"\\n\\n# Tools\\n\\nYou may call one or more functions to assist with the user query.\\n\\nYou are provided with function signatures within <tools></tools> XML tags:\\n<tools>\" }}\n    {%- for tool in tools %}\n        {{- \"\\n\" }}\n        {{- tool | tojson }}\n    {%- endfor %}\n    {{- \"\\n</tools>\\n\\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\\n<tool_call>\\n{\\\"name\\\": <function-name>, \\\"arguments\\\": <args-json-object>}\\n</tool_call><|im_end|>\\n\" }}\n{%- else %}\n    {%- if messages[0]['role'] == 'system' %}\n        {{- '<|im_start|>system\\n' + messages[0]['content'] + '<|im_end|>\\n' }}\n    {%- else %}\n        {{- '<|im_start|>system\\nYou are Qwen, created by Alibaba Cloud. You are a helpful assistant.<|im_end|>\\n' }}\n    {%- endif %}\n{%- endif %}\n{%- for message in messages %}\n    {%- if (message.role == \"user\") or (message.role == \"system\" and not loop.first) or (message.role == \"assistant\" and not message.tool_calls) %}\n        {{- '<|im_start|>' + message.role + '\\n' + message.content + '<|im_end|>' + '\\n' }}\n    {%- elif message.role == \"assistant\" %}\n        {{- '<|im_start|>' + message.role }}\n        {%- if message.content %}\n            {{- '\\n' + message.content }}\n        {%- endif %}\n        {%- for tool_call in message.tool_calls %}\n            {%- if tool_call.function is defined %}\n                {%- set tool_call = tool_call.function %}\n            {%- endif %}\n            {{- '\\n<tool_call>\\n{\"name\": \"' }}\n            {{- tool_call.name }}\n            {{- '\", \"arguments\": ' }}\n            {{- tool_call.arguments | tojson }}\n            {{- '}\\n</tool_call>' }}\n        {%- endfor %}\n        {{- '<|im_end|>\\n' }}\n    {%- elif message.role == \"tool\" %}\n        {%- if (loop.index0 == 0) or (messages[loop.index0 - 1].role != \"tool\") %}\n            {{- '<|im_start|>user' }}\n        {%- endif %}\n        {{- '\\n<tool_response>\\n' }}\n        {{- message.content }}\n        {{- '\\n</tool_response>' }}\n        {%- if loop.last or (messages[loop.index0 + 1].role != \"tool\") %}\n            {{- '<|im_end|>\\n' }}\n        {%- endif %}\n    {%- endif %}\n{%- endfor %}\n{%- if add_generation_prompt %}\n    {{- '<|im_start|>assistant\\n' }}\n{%- endif %}\n",
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+}

checkpoint-540/training_args.bin

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checkpoint-600/README.md

@@ -0,0 +1,202 @@
+---
+base_model: Qwen/Qwen2.5-Coder-7B-Instruct
+library_name: peft
+---
+
+# 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 0.12.0

checkpoint-600/adapter_config.json

@@ -0,0 +1,34 @@
+{
+  "alpha_pattern": {},
+  "auto_mapping": null,
+  "base_model_name_or_path": "Qwen/Qwen2.5-Coder-7B-Instruct",
+  "bias": "none",
+  "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_dropout": 0.1,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "r": 16,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "down_proj",
+    "k_proj",
+    "v_proj",
+    "q_proj",
+    "o_proj",
+    "gate_proj",
+    "up_proj"
+  ],
+  "task_type": "CAUSAL_LM",
+  "use_dora": false,
+  "use_rslora": false
+}

checkpoint-600/adapter_model.safetensors

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checkpoint-600/added_tokens.json

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+  "<|file_sep|>": 151664,
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+  "<|fim_suffix|>": 151661,
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+  "<|im_start|>": 151644,
+  "<|image_pad|>": 151655,
+  "<|object_ref_end|>": 151647,
+  "<|object_ref_start|>": 151646,
+  "<|quad_end|>": 151651,
+  "<|quad_start|>": 151650,
+  "<|repo_name|>": 151663,
+  "<|video_pad|>": 151656,
+  "<|vision_end|>": 151653,
+  "<|vision_pad|>": 151654,
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+}

checkpoint-600/optimizer.pt

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checkpoint-600/rng_state_0.pth

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checkpoint-600/rng_state_1.pth

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checkpoint-600/scheduler.pt

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+size 1064

checkpoint-600/special_tokens_map.json

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+{
+  "additional_special_tokens": [
+    "<|im_start|>",
+    "<|im_end|>",
+    "<|object_ref_start|>",
+    "<|object_ref_end|>",
+    "<|box_start|>",
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+    "<|vision_end|>",
+    "<|vision_pad|>",
+    "<|image_pad|>",
+    "<|video_pad|>"
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+    "content": "<|endoftext|>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  }
+}

checkpoint-600/tokenizer.json

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+size 11421896

checkpoint-600/tokenizer_config.json

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+  "add_prefix_space": false,
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+  },
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+    "<|vision_pad|>",
+    "<|image_pad|>",
+    "<|video_pad|>"
+  ],
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+  "chat_template": "{%- if tools %}\n    {{- '<|im_start|>system\\n' }}\n    {%- if messages[0]['role'] == 'system' %}\n        {{- messages[0]['content'] }}\n    {%- else %}\n        {{- 'You are Qwen, created by Alibaba Cloud. You are a helpful assistant.' }}\n    {%- endif %}\n    {{- \"\\n\\n# Tools\\n\\nYou may call one or more functions to assist with the user query.\\n\\nYou are provided with function signatures within <tools></tools> XML tags:\\n<tools>\" }}\n    {%- for tool in tools %}\n        {{- \"\\n\" }}\n        {{- tool | tojson }}\n    {%- endfor %}\n    {{- \"\\n</tools>\\n\\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\\n<tool_call>\\n{\\\"name\\\": <function-name>, \\\"arguments\\\": <args-json-object>}\\n</tool_call><|im_end|>\\n\" }}\n{%- else %}\n    {%- if messages[0]['role'] == 'system' %}\n        {{- '<|im_start|>system\\n' + messages[0]['content'] + '<|im_end|>\\n' }}\n    {%- else %}\n        {{- '<|im_start|>system\\nYou are Qwen, created by Alibaba Cloud. You are a helpful assistant.<|im_end|>\\n' }}\n    {%- endif %}\n{%- endif %}\n{%- for message in messages %}\n    {%- if (message.role == \"user\") or (message.role == \"system\" and not loop.first) or (message.role == \"assistant\" and not message.tool_calls) %}\n        {{- '<|im_start|>' + message.role + '\\n' + message.content + '<|im_end|>' + '\\n' }}\n    {%- elif message.role == \"assistant\" %}\n        {{- '<|im_start|>' + message.role }}\n        {%- if message.content %}\n            {{- '\\n' + message.content }}\n        {%- endif %}\n        {%- for tool_call in message.tool_calls %}\n            {%- if tool_call.function is defined %}\n                {%- set tool_call = tool_call.function %}\n            {%- endif %}\n            {{- '\\n<tool_call>\\n{\"name\": \"' }}\n            {{- tool_call.name }}\n            {{- '\", \"arguments\": ' }}\n            {{- tool_call.arguments | tojson }}\n            {{- '}\\n</tool_call>' }}\n        {%- endfor %}\n        {{- '<|im_end|>\\n' }}\n    {%- elif message.role == \"tool\" %}\n        {%- if (loop.index0 == 0) or (messages[loop.index0 - 1].role != \"tool\") %}\n            {{- '<|im_start|>user' }}\n        {%- endif %}\n        {{- '\\n<tool_response>\\n' }}\n        {{- message.content }}\n        {{- '\\n</tool_response>' }}\n        {%- if loop.last or (messages[loop.index0 + 1].role != \"tool\") %}\n            {{- '<|im_end|>\\n' }}\n        {%- endif %}\n    {%- endif %}\n{%- endfor %}\n{%- if add_generation_prompt %}\n    {{- '<|im_start|>assistant\\n' }}\n{%- endif %}\n",
+  "clean_up_tokenization_spaces": false,
+  "eos_token": "<|im_end|>",
+  "errors": "replace",
+  "extra_special_tokens": {},
+  "model_max_length": 17000,
+  "pad_token": "<|endoftext|>",
+  "padding_side": "right",
+  "split_special_tokens": false,
+  "tokenizer_class": "Qwen2Tokenizer",
+  "unk_token": null
+}

checkpoint-600/training_args.bin

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+size 5688

trainer_log.jsonl

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+{"current_steps": 539, "total_steps": 1200, "loss": 0.1312, "lr": 2.897549220058411e-05, "epoch": 8.847352024922118, "percentage": 44.92, "elapsed_time": "3:17:56", "remaining_time": "4:02:45", "throughput": 3301.9, "total_tokens": 39216048}
+{"current_steps": 540, "total_steps": 1200, "loss": 0.1107, "lr": 2.8910861626005776e-05, "epoch": 8.863966770508826, "percentage": 45.0, "elapsed_time": "3:18:29", "remaining_time": "4:02:36", "throughput": 3301.26, "total_tokens": 39317320}
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+{"current_steps": 542, "total_steps": 1200, "loss": 0.1212, "lr": 2.8781520506180486e-05, "epoch": 8.897196261682243, "percentage": 45.17, "elapsed_time": "3:19:14", "remaining_time": "4:01:53", "throughput": 3300.59, "total_tokens": 39458584}
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+{"current_steps": 547, "total_steps": 1200, "loss": 0.1266, "lr": 2.845772190406798e-05, "epoch": 8.980269989615785, "percentage": 45.58, "elapsed_time": "3:21:14", "remaining_time": "4:00:14", "throughput": 3300.19, "total_tokens": 39848064}
+{"current_steps": 548, "total_steps": 1200, "loss": 0.1199, "lr": 2.8392889310857612e-05, "epoch": 8.996884735202492, "percentage": 45.67, "elapsed_time": "3:21:36", "remaining_time": "3:59:52", "throughput": 3300.19, "total_tokens": 39922288}
+{"current_steps": 549, "total_steps": 1200, "loss": 0.1246, "lr": 2.832803346316381e-05, "epoch": 9.0, "percentage": 45.75, "elapsed_time": "3:21:39", "remaining_time": "3:59:07", "throughput": 3300.27, "total_tokens": 39932640}
+{"current_steps": 550, "total_steps": 1200, "loss": 0.0949, "lr": 2.8263154805501297e-05, "epoch": 9.016614745586708, "percentage": 45.83, "elapsed_time": "3:21:59", "remaining_time": "3:58:43", "throughput": 3300.89, "total_tokens": 40005688}
+{"current_steps": 551, "total_steps": 1200, "loss": 0.1086, "lr": 2.819825378254111e-05, "epoch": 9.033229491173417, "percentage": 45.92, "elapsed_time": "3:22:13", "remaining_time": "3:58:11", "throughput": 3301.32, "total_tokens": 40057120}
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+{"current_steps": 553, "total_steps": 1200, "loss": 0.1297, "lr": 2.8068386420175375e-05, "epoch": 9.066458982346832, "percentage": 46.08, "elapsed_time": "3:22:53", "remaining_time": "3:57:22", "throughput": 3302.03, "total_tokens": 40196928}
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+{"current_steps": 555, "total_steps": 1200, "loss": 0.1145, "lr": 2.7938434936445945e-05, "epoch": 9.09968847352025, "percentage": 46.25, "elapsed_time": "3:23:37", "remaining_time": "3:56:38", "throughput": 3302.65, "total_tokens": 40350080}
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+{"current_steps": 557, "total_steps": 1200, "loss": 0.0915, "lr": 2.780840289403839e-05, "epoch": 9.132917964693666, "percentage": 46.42, "elapsed_time": "3:24:15", "remaining_time": "3:55:47", "throughput": 3303.99, "total_tokens": 40490432}
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+{"current_steps": 576, "total_steps": 1200, "loss": 0.1019, "lr": 2.656976298823284e-05, "epoch": 9.448598130841122, "percentage": 48.0, "elapsed_time": "3:31:19", "remaining_time": "3:48:56", "throughput": 3305.9, "total_tokens": 41917128}
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+{"current_steps": 579, "total_steps": 1200, "loss": 0.1044, "lr": 2.637375449781115e-05, "epoch": 9.498442367601246, "percentage": 48.25, "elapsed_time": "3:32:18", "remaining_time": "3:47:42", "throughput": 3306.65, "total_tokens": 42122072}
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+{"current_steps": 581, "total_steps": 1200, "loss": 0.1046, "lr": 2.624303434671645e-05, "epoch": 9.531671858774663, "percentage": 48.42, "elapsed_time": "3:33:09", "remaining_time": "3:47:06", "throughput": 3306.55, "total_tokens": 42289336}
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+{"current_steps": 600, "total_steps": 1200, "loss": 0.1101, "lr": 2.5e-05, "epoch": 9.847352024922118, "percentage": 50.0, "elapsed_time": "3:40:45", "remaining_time": "3:40:45", "throughput": 3300.8, "total_tokens": 43721408}
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+{"current_steps": 606, "total_steps": 1200, "loss": 0.1064, "lr": 2.460731706720449e-05, "epoch": 9.947040498442368, "percentage": 50.5, "elapsed_time": "3:42:41", "remaining_time": "3:38:16", "throughput": 3301.75, "total_tokens": 44114776}
+{"current_steps": 607, "total_steps": 1200, "loss": 0.1359, "lr": 2.4541876715097432e-05, "epoch": 9.963655244029075, "percentage": 50.58, "elapsed_time": "3:42:57", "remaining_time": "3:37:48", "throughput": 3302.29, "total_tokens": 44175184}
+{"current_steps": 608, "total_steps": 1200, "loss": 0.0915, "lr": 2.447643950291608e-05, "epoch": 9.980269989615785, "percentage": 50.67, "elapsed_time": "3:43:30", "remaining_time": "3:37:37", "throughput": 3300.68, "total_tokens": 44265024}
+{"current_steps": 609, "total_steps": 1200, "loss": 0.1024, "lr": 2.4411005879159753e-05, "epoch": 9.996884735202492, "percentage": 50.75, "elapsed_time": "3:44:00", "remaining_time": "3:37:23", "throughput": 3300.05, "total_tokens": 44355400}
+{"current_steps": 610, "total_steps": 1200, "loss": 0.087, "lr": 2.4345576292303176e-05, "epoch": 10.0, "percentage": 50.83, "elapsed_time": "3:44:04", "remaining_time": "3:36:43", "throughput": 3300.32, "total_tokens": 44370360}
+{"current_steps": 611, "total_steps": 1200, "loss": 0.0902, "lr": 2.4280151190793417e-05, "epoch": 10.016614745586708, "percentage": 50.92, "elapsed_time": "3:44:30", "remaining_time": "3:36:25", "throughput": 3299.69, "total_tokens": 44446816}
+{"current_steps": 612, "total_steps": 1200, "loss": 0.1038, "lr": 2.4214731023046793e-05, "epoch": 10.033229491173417, "percentage": 51.0, "elapsed_time": "3:44:44", "remaining_time": "3:35:55", "throughput": 3300.39, "total_tokens": 44503632}
+{"current_steps": 613, "total_steps": 1200, "loss": 0.1036, "lr": 2.4149316237445812e-05, "epoch": 10.049844236760125, "percentage": 51.08, "elapsed_time": "3:45:11", "remaining_time": "3:35:38", "throughput": 3300.2, "total_tokens": 44590320}
+{"current_steps": 614, "total_steps": 1200, "loss": 0.1014, "lr": 2.408390728233609e-05, "epoch": 10.066458982346832, "percentage": 51.17, "elapsed_time": "3:45:27", "remaining_time": "3:35:10", "throughput": 3301.03, "total_tokens": 44655224}
+{"current_steps": 615, "total_steps": 1200, "loss": 0.1802, "lr": 2.4018504606023293e-05, "epoch": 10.083073727933542, "percentage": 51.25, "elapsed_time": "3:45:53", "remaining_time": "3:34:52", "throughput": 3300.63, "total_tokens": 44736200}
+{"current_steps": 616, "total_steps": 1200, "loss": 0.0907, "lr": 2.3953108656770016e-05, "epoch": 10.09968847352025, "percentage": 51.33, "elapsed_time": "3:46:15", "remaining_time": "3:34:30", "throughput": 3300.44, "total_tokens": 44804416}
+{"current_steps": 617, "total_steps": 1200, "loss": 0.0943, "lr": 2.3887719882792785e-05, "epoch": 10.116303219106957, "percentage": 51.42, "elapsed_time": "3:46:34", "remaining_time": "3:34:05", "throughput": 3300.81, "total_tokens": 44873864}
+{"current_steps": 618, "total_steps": 1200, "loss": 0.1052, "lr": 2.3822338732258937e-05, "epoch": 10.132917964693666, "percentage": 51.5, "elapsed_time": "3:46:51", "remaining_time": "3:33:39", "throughput": 3301.26, "total_tokens": 44936736}
+{"current_steps": 619, "total_steps": 1200, "loss": 0.0812, "lr": 2.3756965653283557e-05, "epoch": 10.149532710280374, "percentage": 51.58, "elapsed_time": "3:47:18", "remaining_time": "3:33:21", "throughput": 3301.38, "total_tokens": 45026952}
+{"current_steps": 620, "total_steps": 1200, "loss": 0.1003, "lr": 2.3691601093926404e-05, "epoch": 10.166147455867081, "percentage": 51.67, "elapsed_time": "3:47:45", "remaining_time": "3:33:04", "throughput": 3300.57, "total_tokens": 45104816}
+{"current_steps": 621, "total_steps": 1200, "loss": 0.0952, "lr": 2.3626245502188864e-05, "epoch": 10.18276220145379, "percentage": 51.75, "elapsed_time": "3:48:10", "remaining_time": "3:32:44", "throughput": 3300.02, "total_tokens": 45177392}
+{"current_steps": 622, "total_steps": 1200, "loss": 0.1141, "lr": 2.3560899326010822e-05, "epoch": 10.199376947040498, "percentage": 51.83, "elapsed_time": "3:48:29", "remaining_time": "3:32:19", "throughput": 3299.64, "total_tokens": 45237200}
+{"current_steps": 623, "total_steps": 1200, "loss": 0.1083, "lr": 2.3495563013267664e-05, "epoch": 10.215991692627206, "percentage": 51.92, "elapsed_time": "3:48:45", "remaining_time": "3:31:51", "throughput": 3300.01, "total_tokens": 45293376}
+{"current_steps": 624, "total_steps": 1200, "loss": 0.1032, "lr": 2.3430237011767167e-05, "epoch": 10.232606438213915, "percentage": 52.0, "elapsed_time": "3:49:08", "remaining_time": "3:31:30", "throughput": 3299.98, "total_tokens": 45369376}
+{"current_steps": 625, "total_steps": 1200, "loss": 0.0921, "lr": 2.3364921769246423e-05, "epoch": 10.249221183800623, "percentage": 52.08, "elapsed_time": "3:49:33", "remaining_time": "3:31:11", "throughput": 3299.08, "total_tokens": 45439920}