Upload folder using huggingface_hub

.gitattributes

@@ -65,3 +65,7 @@ checkpoint-1000/tokenizer.json filter=lfs diff=lfs merge=lfs -text
 checkpoint-250/tokenizer.json filter=lfs diff=lfs merge=lfs -text
 checkpoint-500/tokenizer.json filter=lfs diff=lfs merge=lfs -text
 checkpoint-750/tokenizer.json filter=lfs diff=lfs merge=lfs -text
+baseline-qwen2vl_sft-sft_colqwen-k2-train-29-APRIL-0_3/checkpoint-1000/tokenizer.json filter=lfs diff=lfs merge=lfs -text
+baseline-qwen2vl_sft-sft_colqwen-k2-train-29-APRIL-0_3/checkpoint-250/tokenizer.json filter=lfs diff=lfs merge=lfs -text
+baseline-qwen2vl_sft-sft_colqwen-k2-train-29-APRIL-0_3/checkpoint-500/tokenizer.json filter=lfs diff=lfs merge=lfs -text
+baseline-qwen2vl_sft-sft_colqwen-k2-train-29-APRIL-0_3/checkpoint-750/tokenizer.json filter=lfs diff=lfs merge=lfs -text

baseline-qwen2vl_sft-sft_colqwen-k2-train-29-APRIL-0_3/checkpoint-1000/README.md

@@ -0,0 +1,202 @@
+---
+base_model: Qwen/Qwen2.5-VL-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 0.15.2

baseline-qwen2vl_sft-sft_colqwen-k2-train-29-APRIL-0_3/checkpoint-1000/adapter_config.json

@@ -0,0 +1,34 @@
+{
+  "alpha_pattern": {},
+  "auto_mapping": null,
+  "base_model_name_or_path": "Qwen/Qwen2.5-VL-7B-Instruct",
+  "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": 16,
+  "lora_bias": false,
+  "lora_dropout": 0.05,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "r": 8,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "q_proj",
+    "v_proj"
+  ],
+  "task_type": "CAUSAL_LM",
+  "trainable_token_indices": null,
+  "use_dora": false,
+  "use_rslora": false
+}

baseline-qwen2vl_sft-sft_colqwen-k2-train-29-APRIL-0_3/checkpoint-1000/adapter_model.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:8601bfe73b8f37d53798fb9d82734a77e9afbec16b714f79e4863b875e073e1b
+size 10107280

baseline-qwen2vl_sft-sft_colqwen-k2-train-29-APRIL-0_3/checkpoint-1000/added_tokens.json

@@ -0,0 +1,24 @@
+{
+  "</tool_call>": 151658,
+  "<tool_call>": 151657,
+  "<|box_end|>": 151649,
+  "<|box_start|>": 151648,
+  "<|endoftext|>": 151643,
+  "<|file_sep|>": 151664,
+  "<|fim_middle|>": 151660,
+  "<|fim_pad|>": 151662,
+  "<|fim_prefix|>": 151659,
+  "<|fim_suffix|>": 151661,
+  "<|im_end|>": 151645,
+  "<|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,
+  "<|vision_start|>": 151652
+}

baseline-qwen2vl_sft-sft_colqwen-k2-train-29-APRIL-0_3/checkpoint-1000/optimizer.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:8f6a99364bbb000c7dcef57851d3315ce9f1d6316dc713308afe498c5608bbdd
+size 20279354

baseline-qwen2vl_sft-sft_colqwen-k2-train-29-APRIL-0_3/checkpoint-1000/rng_state.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:d01f01453677505af4aa11c7850642575f56bce3e76e1eac2393bee448a0e540
+size 14244

baseline-qwen2vl_sft-sft_colqwen-k2-train-29-APRIL-0_3/checkpoint-1000/scheduler.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:250808f4d22322244aa9e9fd377fc2f92b37d5d5e6f6cc7ac62f86ce40c2dce7
+size 1064

baseline-qwen2vl_sft-sft_colqwen-k2-train-29-APRIL-0_3/checkpoint-1000/special_tokens_map.json

@@ -0,0 +1,31 @@
+{
+  "additional_special_tokens": [
+    "<|im_start|>",
+    "<|im_end|>",
+    "<|object_ref_start|>",
+    "<|object_ref_end|>",
+    "<|box_start|>",
+    "<|box_end|>",
+    "<|quad_start|>",
+    "<|quad_end|>",
+    "<|vision_start|>",
+    "<|vision_end|>",
+    "<|vision_pad|>",
+    "<|image_pad|>",
+    "<|video_pad|>"
+  ],
+  "eos_token": {
+    "content": "<|im_end|>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "pad_token": {
+    "content": "<|endoftext|>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  }
+}

baseline-qwen2vl_sft-sft_colqwen-k2-train-29-APRIL-0_3/checkpoint-1000/tokenizer.json

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:9c5ae00e602b8860cbd784ba82a8aa14e8feecec692e7076590d014d7b7fdafa
+size 11421896

baseline-qwen2vl_sft-sft_colqwen-k2-train-29-APRIL-0_3/checkpoint-1000/tokenizer_config.json

@@ -0,0 +1,208 @@
+{
+  "add_bos_token": false,
+  "add_prefix_space": false,
+  "added_tokens_decoder": {
+    "151643": {
+      "content": "<|endoftext|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151644": {
+      "content": "<|im_start|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151645": {
+      "content": "<|im_end|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151646": {
+      "content": "<|object_ref_start|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151647": {
+      "content": "<|object_ref_end|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151648": {
+      "content": "<|box_start|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151649": {
+      "content": "<|box_end|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151650": {
+      "content": "<|quad_start|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151651": {
+      "content": "<|quad_end|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151652": {
+      "content": "<|vision_start|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151653": {
+      "content": "<|vision_end|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151654": {
+      "content": "<|vision_pad|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151655": {
+      "content": "<|image_pad|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151656": {
+      "content": "<|video_pad|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151657": {
+      "content": "<tool_call>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151658": {
+      "content": "</tool_call>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151659": {
+      "content": "<|fim_prefix|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151660": {
+      "content": "<|fim_middle|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151661": {
+      "content": "<|fim_suffix|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151662": {
+      "content": "<|fim_pad|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151663": {
+      "content": "<|repo_name|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151664": {
+      "content": "<|file_sep|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    }
+  },
+  "additional_special_tokens": [
+    "<|im_start|>",
+    "<|im_end|>",
+    "<|object_ref_start|>",
+    "<|object_ref_end|>",
+    "<|box_start|>",
+    "<|box_end|>",
+    "<|quad_start|>",
+    "<|quad_end|>",
+    "<|vision_start|>",
+    "<|vision_end|>",
+    "<|vision_pad|>",
+    "<|image_pad|>",
+    "<|video_pad|>"
+  ],
+  "bos_token": null,
+  "chat_template": "{% set image_count = namespace(value=0) %}{% set video_count = namespace(value=0) %}{% for message in messages %}{% if loop.first and message['role'] != 'system' %}<|im_start|>system\nYou are a helpful assistant.<|im_end|>\n{% endif %}<|im_start|>{{ message['role'] }}\n{% if message['content'] is string %}{{ message['content'] }}<|im_end|>\n{% else %}{% for content in message['content'] %}{% if content['type'] == 'image' or 'image' in content or 'image_url' in content %}{% set image_count.value = image_count.value + 1 %}{% if add_vision_id %}Picture {{ image_count.value }}: {% endif %}<|vision_start|><|image_pad|><|vision_end|>{% elif content['type'] == 'video' or 'video' in content %}{% set video_count.value = video_count.value + 1 %}{% if add_vision_id %}Video {{ video_count.value }}: {% endif %}<|vision_start|><|video_pad|><|vision_end|>{% elif 'text' in content %}{{ content['text'] }}{% endif %}{% endfor %}<|im_end|>\n{% endif %}{% endfor %}{% if add_generation_prompt %}<|im_start|>assistant\n{% endif %}",
+  "clean_up_tokenization_spaces": false,
+  "eos_token": "<|im_end|>",
+  "errors": "replace",
+  "extra_special_tokens": {},
+  "model_max_length": 131072,
+  "pad_token": "<|endoftext|>",
+  "split_special_tokens": false,
+  "tokenizer_class": "Qwen2Tokenizer",
+  "unk_token": null
+}

baseline-qwen2vl_sft-sft_colqwen-k2-train-29-APRIL-0_3/checkpoint-1000/training_args.bin

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:be8d81f76a78ae3475b48f07cad8c818b7d053e9df8d0311b83fc183e0d06528
+size 5816

baseline-qwen2vl_sft-sft_colqwen-k2-train-29-APRIL-0_3/checkpoint-250/README.md

@@ -0,0 +1,202 @@
+---
+base_model: Qwen/Qwen2.5-VL-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 0.15.2

baseline-qwen2vl_sft-sft_colqwen-k2-train-29-APRIL-0_3/checkpoint-250/adapter_config.json

@@ -0,0 +1,34 @@
+{
+  "alpha_pattern": {},
+  "auto_mapping": null,
+  "base_model_name_or_path": "Qwen/Qwen2.5-VL-7B-Instruct",
+  "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": 16,
+  "lora_bias": false,
+  "lora_dropout": 0.05,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "r": 8,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "q_proj",
+    "v_proj"
+  ],
+  "task_type": "CAUSAL_LM",
+  "trainable_token_indices": null,
+  "use_dora": false,
+  "use_rslora": false
+}

baseline-qwen2vl_sft-sft_colqwen-k2-train-29-APRIL-0_3/checkpoint-250/adapter_model.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:886acd7524fe7fce8d5daf465778b18f4212e20c367d3898ebbee11ee4ba678e
+size 10107280

baseline-qwen2vl_sft-sft_colqwen-k2-train-29-APRIL-0_3/checkpoint-250/added_tokens.json

@@ -0,0 +1,24 @@
+{
+  "</tool_call>": 151658,
+  "<tool_call>": 151657,
+  "<|box_end|>": 151649,
+  "<|box_start|>": 151648,
+  "<|endoftext|>": 151643,
+  "<|file_sep|>": 151664,
+  "<|fim_middle|>": 151660,
+  "<|fim_pad|>": 151662,
+  "<|fim_prefix|>": 151659,
+  "<|fim_suffix|>": 151661,
+  "<|im_end|>": 151645,
+  "<|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,
+  "<|vision_start|>": 151652
+}

baseline-qwen2vl_sft-sft_colqwen-k2-train-29-APRIL-0_3/checkpoint-250/optimizer.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:3248fb14a232fc30a934da5952e161ac43bfd86a706acdfe8a939062f8ef66c9
+size 20279354

baseline-qwen2vl_sft-sft_colqwen-k2-train-29-APRIL-0_3/checkpoint-250/rng_state.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:0edbb50ccf89eb8543453db660e13e3acfca9f97cbd60c80d902a6f7bae6c276
+size 14244

baseline-qwen2vl_sft-sft_colqwen-k2-train-29-APRIL-0_3/checkpoint-250/scheduler.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:26b0f38577550e6ec2e1e288967c2288fd5a2c13e848d2c3aaf444b917f2052e
+size 1064

baseline-qwen2vl_sft-sft_colqwen-k2-train-29-APRIL-0_3/checkpoint-250/special_tokens_map.json

@@ -0,0 +1,31 @@
+{
+  "additional_special_tokens": [
+    "<|im_start|>",
+    "<|im_end|>",
+    "<|object_ref_start|>",
+    "<|object_ref_end|>",
+    "<|box_start|>",
+    "<|box_end|>",
+    "<|quad_start|>",
+    "<|quad_end|>",
+    "<|vision_start|>",
+    "<|vision_end|>",
+    "<|vision_pad|>",
+    "<|image_pad|>",
+    "<|video_pad|>"
+  ],
+  "eos_token": {
+    "content": "<|im_end|>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "pad_token": {
+    "content": "<|endoftext|>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  }
+}

baseline-qwen2vl_sft-sft_colqwen-k2-train-29-APRIL-0_3/checkpoint-250/tokenizer.json

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:9c5ae00e602b8860cbd784ba82a8aa14e8feecec692e7076590d014d7b7fdafa
+size 11421896

baseline-qwen2vl_sft-sft_colqwen-k2-train-29-APRIL-0_3/checkpoint-250/tokenizer_config.json

@@ -0,0 +1,208 @@
+{
+  "add_bos_token": false,
+  "add_prefix_space": false,
+  "added_tokens_decoder": {
+    "151643": {
+      "content": "<|endoftext|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151644": {
+      "content": "<|im_start|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151645": {
+      "content": "<|im_end|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151646": {
+      "content": "<|object_ref_start|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151647": {
+      "content": "<|object_ref_end|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151648": {
+      "content": "<|box_start|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151649": {
+      "content": "<|box_end|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151650": {
+      "content": "<|quad_start|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151651": {
+      "content": "<|quad_end|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151652": {
+      "content": "<|vision_start|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151653": {
+      "content": "<|vision_end|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151654": {
+      "content": "<|vision_pad|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151655": {
+      "content": "<|image_pad|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151656": {
+      "content": "<|video_pad|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151657": {
+      "content": "<tool_call>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151658": {
+      "content": "</tool_call>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151659": {
+      "content": "<|fim_prefix|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151660": {
+      "content": "<|fim_middle|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151661": {
+      "content": "<|fim_suffix|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151662": {
+      "content": "<|fim_pad|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151663": {
+      "content": "<|repo_name|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151664": {
+      "content": "<|file_sep|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    }
+  },
+  "additional_special_tokens": [
+    "<|im_start|>",
+    "<|im_end|>",
+    "<|object_ref_start|>",
+    "<|object_ref_end|>",
+    "<|box_start|>",
+    "<|box_end|>",
+    "<|quad_start|>",
+    "<|quad_end|>",
+    "<|vision_start|>",
+    "<|vision_end|>",
+    "<|vision_pad|>",
+    "<|image_pad|>",
+    "<|video_pad|>"
+  ],
+  "bos_token": null,
+  "chat_template": "{% set image_count = namespace(value=0) %}{% set video_count = namespace(value=0) %}{% for message in messages %}{% if loop.first and message['role'] != 'system' %}<|im_start|>system\nYou are a helpful assistant.<|im_end|>\n{% endif %}<|im_start|>{{ message['role'] }}\n{% if message['content'] is string %}{{ message['content'] }}<|im_end|>\n{% else %}{% for content in message['content'] %}{% if content['type'] == 'image' or 'image' in content or 'image_url' in content %}{% set image_count.value = image_count.value + 1 %}{% if add_vision_id %}Picture {{ image_count.value }}: {% endif %}<|vision_start|><|image_pad|><|vision_end|>{% elif content['type'] == 'video' or 'video' in content %}{% set video_count.value = video_count.value + 1 %}{% if add_vision_id %}Video {{ video_count.value }}: {% endif %}<|vision_start|><|video_pad|><|vision_end|>{% elif 'text' in content %}{{ content['text'] }}{% endif %}{% endfor %}<|im_end|>\n{% endif %}{% endfor %}{% if add_generation_prompt %}<|im_start|>assistant\n{% endif %}",
+  "clean_up_tokenization_spaces": false,
+  "eos_token": "<|im_end|>",
+  "errors": "replace",
+  "extra_special_tokens": {},
+  "model_max_length": 131072,
+  "pad_token": "<|endoftext|>",
+  "split_special_tokens": false,
+  "tokenizer_class": "Qwen2Tokenizer",
+  "unk_token": null
+}

baseline-qwen2vl_sft-sft_colqwen-k2-train-29-APRIL-0_3/checkpoint-250/trainer_state.json

@@ -0,0 +1,2284 @@
+{
+  "best_global_step": null,
+  "best_metric": null,
+  "best_model_checkpoint": null,
+  "epoch": 0.05,
+  "eval_steps": 500,
+  "global_step": 250,
+  "is_hyper_param_search": false,
+  "is_local_process_zero": true,
+  "is_world_process_zero": true,
+  "log_history": [
+    {
+      "epoch": 0.0002,
+      "grad_norm": 5.698113441467285,
+      "learning_rate": 5e-06,
+      "loss": 12.2509,
+      "mean_token_accuracy": 0.2450142428278923,
+      "num_tokens": 16438.0,
+      "step": 1
+    },
+    {
+      "epoch": 0.0004,
+      "grad_norm": 6.063949108123779,
+      "learning_rate": 4.999000000000001e-06,
+      "loss": 13.3748,
+      "mean_token_accuracy": 0.2325708046555519,
+      "num_tokens": 31368.0,
+      "step": 2
+    },
+    {
+      "epoch": 0.0006,
+      "grad_norm": 8.026069641113281,
+      "learning_rate": 4.998e-06,
+      "loss": 12.5454,
+      "mean_token_accuracy": 0.2398785501718521,
+      "num_tokens": 58542.0,
+      "step": 3
+    },
+    {
+      "epoch": 0.0008,
+      "grad_norm": 6.758559703826904,
+      "learning_rate": 4.997000000000001e-06,
+      "loss": 13.9155,
+      "mean_token_accuracy": 0.21041666716337204,
+      "num_tokens": 77844.0,
+      "step": 4
+    },
+    {
+      "epoch": 0.001,
+      "grad_norm": 6.786197185516357,
+      "learning_rate": 4.996e-06,
+      "loss": 13.2561,
+      "mean_token_accuracy": 0.1967741921544075,
+      "num_tokens": 89661.0,
+      "step": 5
+    },
+    {
+      "epoch": 0.0012,
+      "grad_norm": 9.514345169067383,
+      "learning_rate": 4.9950000000000005e-06,
+      "loss": 12.3378,
+      "mean_token_accuracy": 0.20638945698738098,
+      "num_tokens": 104612.0,
+      "step": 6
+    },
+    {
+      "epoch": 0.0014,
+      "grad_norm": 7.438795566558838,
+      "learning_rate": 4.994000000000001e-06,
+      "loss": 12.0814,
+      "mean_token_accuracy": 0.2916666716337204,
+      "num_tokens": 114269.0,
+      "step": 7
+    },
+    {
+      "epoch": 0.0016,
+      "grad_norm": 15.847832679748535,
+      "learning_rate": 4.993e-06,
+      "loss": 13.2761,
+      "mean_token_accuracy": 0.2450142428278923,
+      "num_tokens": 128762.0,
+      "step": 8
+    },
+    {
+      "epoch": 0.0018,
+      "grad_norm": 7.620685577392578,
+      "learning_rate": 4.992e-06,
+      "loss": 13.1792,
+      "mean_token_accuracy": 0.2165178582072258,
+      "num_tokens": 148453.0,
+      "step": 9
+    },
+    {
+      "epoch": 0.002,
+      "grad_norm": 8.26969051361084,
+      "learning_rate": 4.991e-06,
+      "loss": 12.853,
+      "mean_token_accuracy": 0.21405228972434998,
+      "num_tokens": 167693.0,
+      "step": 10
+    },
+    {
+      "epoch": 0.0022,
+      "grad_norm": 7.328786373138428,
+      "learning_rate": 4.9900000000000005e-06,
+      "loss": 12.9578,
+      "mean_token_accuracy": 0.2115987464785576,
+      "num_tokens": 182157.0,
+      "step": 11
+    },
+    {
+      "epoch": 0.0024,
+      "grad_norm": 7.058177947998047,
+      "learning_rate": 4.989000000000001e-06,
+      "loss": 12.7711,
+      "mean_token_accuracy": 0.2002224698662758,
+      "num_tokens": 201457.0,
+      "step": 12
+    },
+    {
+      "epoch": 0.0026,
+      "grad_norm": 6.48744010925293,
+      "learning_rate": 4.988e-06,
+      "loss": 13.006,
+      "mean_token_accuracy": 0.23790322244167328,
+      "num_tokens": 215922.0,
+      "step": 13
+    },
+    {
+      "epoch": 0.0028,
+      "grad_norm": 6.006223201751709,
+      "learning_rate": 4.987e-06,
+      "loss": 10.5975,
+      "mean_token_accuracy": 0.2096899226307869,
+      "num_tokens": 225597.0,
+      "step": 14
+    },
+    {
+      "epoch": 0.003,
+      "grad_norm": 6.274689674377441,
+      "learning_rate": 4.986e-06,
+      "loss": 11.2766,
+      "mean_token_accuracy": 0.26851852238178253,
+      "num_tokens": 240100.0,
+      "step": 15
+    },
+    {
+      "epoch": 0.0032,
+      "grad_norm": 8.211908340454102,
+      "learning_rate": 4.9850000000000006e-06,
+      "loss": 13.7091,
+      "mean_token_accuracy": 0.20202020555734634,
+      "num_tokens": 259400.0,
+      "step": 16
+    },
+    {
+      "epoch": 0.0034,
+      "grad_norm": 6.356493949890137,
+      "learning_rate": 4.984000000000001e-06,
+      "loss": 12.043,
+      "mean_token_accuracy": 0.20519480854272842,
+      "num_tokens": 278628.0,
+      "step": 17
+    },
+    {
+      "epoch": 0.0036,
+      "grad_norm": 6.438048839569092,
+      "learning_rate": 4.983e-06,
+      "loss": 11.5484,
+      "mean_token_accuracy": 0.2343137264251709,
+      "num_tokens": 303856.0,
+      "step": 18
+    },
+    {
+      "epoch": 0.0038,
+      "grad_norm": 7.152822494506836,
+      "learning_rate": 4.982e-06,
+      "loss": 13.4607,
+      "mean_token_accuracy": 0.17500000447034836,
+      "num_tokens": 318686.0,
+      "step": 19
+    },
+    {
+      "epoch": 0.004,
+      "grad_norm": 6.464632034301758,
+      "learning_rate": 4.981e-06,
+      "loss": 11.7533,
+      "mean_token_accuracy": 0.21959459781646729,
+      "num_tokens": 337999.0,
+      "step": 20
+    },
+    {
+      "epoch": 0.0042,
+      "grad_norm": 7.051283836364746,
+      "learning_rate": 4.980000000000001e-06,
+      "loss": 12.9788,
+      "mean_token_accuracy": 0.22011494636535645,
+      "num_tokens": 356602.0,
+      "step": 21
+    },
+    {
+      "epoch": 0.0044,
+      "grad_norm": 9.595747947692871,
+      "learning_rate": 4.979e-06,
+      "loss": 10.9347,
+      "mean_token_accuracy": 0.2645348906517029,
+      "num_tokens": 373201.0,
+      "step": 22
+    },
+    {
+      "epoch": 0.0046,
+      "grad_norm": 7.404125213623047,
+      "learning_rate": 4.9780000000000005e-06,
+      "loss": 12.5181,
+      "mean_token_accuracy": 0.2666666731238365,
+      "num_tokens": 387660.0,
+      "step": 23
+    },
+    {
+      "epoch": 0.0048,
+      "grad_norm": 6.656332969665527,
+      "learning_rate": 4.977e-06,
+      "loss": 11.5566,
+      "mean_token_accuracy": 0.209001787006855,
+      "num_tokens": 402129.0,
+      "step": 24
+    },
+    {
+      "epoch": 0.005,
+      "grad_norm": 6.866989612579346,
+      "learning_rate": 4.976e-06,
+      "loss": 12.4797,
+      "mean_token_accuracy": 0.2379310354590416,
+      "num_tokens": 421133.0,
+      "step": 25
+    },
+    {
+      "epoch": 0.0052,
+      "grad_norm": 6.77735710144043,
+      "learning_rate": 4.975000000000001e-06,
+      "loss": 13.6256,
+      "mean_token_accuracy": 0.22177419066429138,
+      "num_tokens": 440531.0,
+      "step": 26
+    },
+    {
+      "epoch": 0.0054,
+      "grad_norm": 8.206353187561035,
+      "learning_rate": 4.974e-06,
+      "loss": 13.0667,
+      "mean_token_accuracy": 0.21791187673807144,
+      "num_tokens": 459798.0,
+      "step": 27
+    },
+    {
+      "epoch": 0.0056,
+      "grad_norm": 7.40612268447876,
+      "learning_rate": 4.9730000000000005e-06,
+      "loss": 13.5884,
+      "mean_token_accuracy": 0.19052419066429138,
+      "num_tokens": 478587.0,
+      "step": 28
+    },
+    {
+      "epoch": 0.0058,
+      "grad_norm": 6.71999454498291,
+      "learning_rate": 4.972e-06,
+      "loss": 12.0322,
+      "mean_token_accuracy": 0.24526315927505493,
+      "num_tokens": 492356.0,
+      "step": 29
+    },
+    {
+      "epoch": 0.006,
+      "grad_norm": 8.108094215393066,
+      "learning_rate": 4.971e-06,
+      "loss": 12.4858,
+      "mean_token_accuracy": 0.2566666677594185,
+      "num_tokens": 507242.0,
+      "step": 30
+    },
+    {
+      "epoch": 0.0062,
+      "grad_norm": 7.7994513511657715,
+      "learning_rate": 4.970000000000001e-06,
+      "loss": 13.0762,
+      "mean_token_accuracy": 0.24568965286016464,
+      "num_tokens": 525987.0,
+      "step": 31
+    },
+    {
+      "epoch": 0.0064,
+      "grad_norm": 7.258217811584473,
+      "learning_rate": 4.969e-06,
+      "loss": 12.7757,
+      "mean_token_accuracy": 0.24137930572032928,
+      "num_tokens": 540447.0,
+      "step": 32
+    },
+    {
+      "epoch": 0.0066,
+      "grad_norm": 14.746047973632812,
+      "learning_rate": 4.9680000000000005e-06,
+      "loss": 14.4335,
+      "mean_token_accuracy": 0.22649572789669037,
+      "num_tokens": 560131.0,
+      "step": 33
+    },
+    {
+      "epoch": 0.0068,
+      "grad_norm": 5.289712429046631,
+      "learning_rate": 4.967e-06,
+      "loss": 9.6693,
+      "mean_token_accuracy": 0.2875000089406967,
+      "num_tokens": 579313.0,
+      "step": 34
+    },
+    {
+      "epoch": 0.007,
+      "grad_norm": 7.960392951965332,
+      "learning_rate": 4.966e-06,
+      "loss": 13.1738,
+      "mean_token_accuracy": 0.25833334028720856,
+      "num_tokens": 598611.0,
+      "step": 35
+    },
+    {
+      "epoch": 0.0072,
+      "grad_norm": 8.295417785644531,
+      "learning_rate": 4.965000000000001e-06,
+      "loss": 11.8889,
+      "mean_token_accuracy": 0.24144145101308823,
+      "num_tokens": 615588.0,
+      "step": 36
+    },
+    {
+      "epoch": 0.0074,
+      "grad_norm": 7.051126480102539,
+      "learning_rate": 4.964e-06,
+      "loss": 12.1364,
+      "mean_token_accuracy": 0.23590733855962753,
+      "num_tokens": 636032.0,
+      "step": 37
+    },
+    {
+      "epoch": 0.0076,
+      "grad_norm": 7.895816326141357,
+      "learning_rate": 4.963000000000001e-06,
+      "loss": 12.8971,
+      "mean_token_accuracy": 0.18571428954601288,
+      "num_tokens": 655299.0,
+      "step": 38
+    },
+    {
+      "epoch": 0.0078,
+      "grad_norm": 7.544738292694092,
+      "learning_rate": 4.962e-06,
+      "loss": 13.0581,
+      "mean_token_accuracy": 0.20937500149011612,
+      "num_tokens": 674357.0,
+      "step": 39
+    },
+    {
+      "epoch": 0.008,
+      "grad_norm": 7.548039436340332,
+      "learning_rate": 4.9610000000000004e-06,
+      "loss": 13.2158,
+      "mean_token_accuracy": 0.20892494916915894,
+      "num_tokens": 693698.0,
+      "step": 40
+    },
+    {
+      "epoch": 0.0082,
+      "grad_norm": 7.687658309936523,
+      "learning_rate": 4.960000000000001e-06,
+      "loss": 12.8524,
+      "mean_token_accuracy": 0.28735632449388504,
+      "num_tokens": 703433.0,
+      "step": 41
+    },
+    {
+      "epoch": 0.0084,
+      "grad_norm": 8.011468887329102,
+      "learning_rate": 4.959e-06,
+      "loss": 13.5655,
+      "mean_token_accuracy": 0.21635150164365768,
+      "num_tokens": 722733.0,
+      "step": 42
+    },
+    {
+      "epoch": 0.0086,
+      "grad_norm": 11.084840774536133,
+      "learning_rate": 4.958000000000001e-06,
+      "loss": 12.7054,
+      "mean_token_accuracy": 0.21746384352445602,
+      "num_tokens": 738121.0,
+      "step": 43
+    },
+    {
+      "epoch": 0.0088,
+      "grad_norm": 9.436426162719727,
+      "learning_rate": 4.957e-06,
+      "loss": 13.5213,
+      "mean_token_accuracy": 0.22783251106739044,
+      "num_tokens": 757723.0,
+      "step": 44
+    },
+    {
+      "epoch": 0.009,
+      "grad_norm": 8.382990837097168,
+      "learning_rate": 4.9560000000000005e-06,
+      "loss": 12.6328,
+      "mean_token_accuracy": 0.2567741870880127,
+      "num_tokens": 772646.0,
+      "step": 45
+    },
+    {
+      "epoch": 0.0092,
+      "grad_norm": 8.272336959838867,
+      "learning_rate": 4.955e-06,
+      "loss": 13.0365,
+      "mean_token_accuracy": 0.2611111178994179,
+      "num_tokens": 792334.0,
+      "step": 46
+    },
+    {
+      "epoch": 0.0094,
+      "grad_norm": 10.347405433654785,
+      "learning_rate": 4.954e-06,
+      "loss": 12.8164,
+      "mean_token_accuracy": 0.22616633027791977,
+      "num_tokens": 811713.0,
+      "step": 47
+    },
+    {
+      "epoch": 0.0096,
+      "grad_norm": 7.27515983581543,
+      "learning_rate": 4.953000000000001e-06,
+      "loss": 11.0123,
+      "mean_token_accuracy": 0.23790322244167328,
+      "num_tokens": 832998.0,
+      "step": 48
+    },
+    {
+      "epoch": 0.0098,
+      "grad_norm": 8.973237991333008,
+      "learning_rate": 4.952e-06,
+      "loss": 12.9664,
+      "mean_token_accuracy": 0.19805195182561874,
+      "num_tokens": 861717.0,
+      "step": 49
+    },
+    {
+      "epoch": 0.01,
+      "grad_norm": 8.738320350646973,
+      "learning_rate": 4.9510000000000005e-06,
+      "loss": 12.5728,
+      "mean_token_accuracy": 0.24344827979803085,
+      "num_tokens": 875736.0,
+      "step": 50
+    },
+    {
+      "epoch": 0.0102,
+      "grad_norm": 8.51733112335205,
+      "learning_rate": 4.95e-06,
+      "loss": 12.7596,
+      "mean_token_accuracy": 0.22380952537059784,
+      "num_tokens": 894386.0,
+      "step": 51
+    },
+    {
+      "epoch": 0.0104,
+      "grad_norm": 8.787413597106934,
+      "learning_rate": 4.949e-06,
+      "loss": 12.4493,
+      "mean_token_accuracy": 0.268075630068779,
+      "num_tokens": 908848.0,
+      "step": 52
+    },
+    {
+      "epoch": 0.0106,
+      "grad_norm": 7.849542617797852,
+      "learning_rate": 4.948000000000001e-06,
+      "loss": 12.7514,
+      "mean_token_accuracy": 0.23790322244167328,
+      "num_tokens": 923309.0,
+      "step": 53
+    },
+    {
+      "epoch": 0.0108,
+      "grad_norm": 8.378942489624023,
+      "learning_rate": 4.947e-06,
+      "loss": 11.4953,
+      "mean_token_accuracy": 0.2290322557091713,
+      "num_tokens": 938298.0,
+      "step": 54
+    },
+    {
+      "epoch": 0.011,
+      "grad_norm": 8.311882972717285,
+      "learning_rate": 4.946000000000001e-06,
+      "loss": 12.0904,
+      "mean_token_accuracy": 0.24014336615800858,
+      "num_tokens": 948288.0,
+      "step": 55
+    },
+    {
+      "epoch": 0.0112,
+      "grad_norm": 9.599881172180176,
+      "learning_rate": 4.945e-06,
+      "loss": 14.3569,
+      "mean_token_accuracy": 0.22649572789669037,
+      "num_tokens": 967543.0,
+      "step": 56
+    },
+    {
+      "epoch": 0.0114,
+      "grad_norm": 8.84776496887207,
+      "learning_rate": 4.9440000000000004e-06,
+      "loss": 12.2268,
+      "mean_token_accuracy": 0.28287841379642487,
+      "num_tokens": 981726.0,
+      "step": 57
+    },
+    {
+      "epoch": 0.0116,
+      "grad_norm": 11.259871482849121,
+      "learning_rate": 4.943000000000001e-06,
+      "loss": 12.6356,
+      "mean_token_accuracy": 0.22177419066429138,
+      "num_tokens": 996225.0,
+      "step": 58
+    },
+    {
+      "epoch": 0.0118,
+      "grad_norm": 10.529711723327637,
+      "learning_rate": 4.942e-06,
+      "loss": 11.9829,
+      "mean_token_accuracy": 0.26986077427864075,
+      "num_tokens": 1015573.0,
+      "step": 59
+    },
+    {
+      "epoch": 0.012,
+      "grad_norm": 8.90577220916748,
+      "learning_rate": 4.941000000000001e-06,
+      "loss": 11.4895,
+      "mean_token_accuracy": 0.2374911978840828,
+      "num_tokens": 1034198.0,
+      "step": 60
+    },
+    {
+      "epoch": 0.0122,
+      "grad_norm": 7.851955413818359,
+      "learning_rate": 4.94e-06,
+      "loss": 12.0083,
+      "mean_token_accuracy": 0.22478991746902466,
+      "num_tokens": 1045419.0,
+      "step": 61
+    },
+    {
+      "epoch": 0.0124,
+      "grad_norm": 9.812698364257812,
+      "learning_rate": 4.9390000000000005e-06,
+      "loss": 12.9777,
+      "mean_token_accuracy": 0.2379310354590416,
+      "num_tokens": 1064723.0,
+      "step": 62
+    },
+    {
+      "epoch": 0.0126,
+      "grad_norm": 8.35107707977295,
+      "learning_rate": 4.938000000000001e-06,
+      "loss": 11.3187,
+      "mean_token_accuracy": 0.24358975142240524,
+      "num_tokens": 1079171.0,
+      "step": 63
+    },
+    {
+      "epoch": 0.0128,
+      "grad_norm": 7.16640567779541,
+      "learning_rate": 4.937e-06,
+      "loss": 10.2182,
+      "mean_token_accuracy": 0.34151194989681244,
+      "num_tokens": 1093695.0,
+      "step": 64
+    },
+    {
+      "epoch": 0.013,
+      "grad_norm": 10.18386459350586,
+      "learning_rate": 4.936e-06,
+      "loss": 12.2175,
+      "mean_token_accuracy": 0.25961539149284363,
+      "num_tokens": 1108580.0,
+      "step": 65
+    },
+    {
+      "epoch": 0.0132,
+      "grad_norm": 8.232446670532227,
+      "learning_rate": 4.935e-06,
+      "loss": 11.8182,
+      "mean_token_accuracy": 0.27314814925193787,
+      "num_tokens": 1123098.0,
+      "step": 66
+    },
+    {
+      "epoch": 0.0134,
+      "grad_norm": 8.809263229370117,
+      "learning_rate": 4.9340000000000005e-06,
+      "loss": 10.9148,
+      "mean_token_accuracy": 0.20927418768405914,
+      "num_tokens": 1137548.0,
+      "step": 67
+    },
+    {
+      "epoch": 0.0136,
+      "grad_norm": 9.865777015686035,
+      "learning_rate": 4.933000000000001e-06,
+      "loss": 12.6294,
+      "mean_token_accuracy": 0.22962962836027145,
+      "num_tokens": 1156845.0,
+      "step": 68
+    },
+    {
+      "epoch": 0.0138,
+      "grad_norm": 7.259024620056152,
+      "learning_rate": 4.932e-06,
+      "loss": 9.7717,
+      "mean_token_accuracy": 0.26875001192092896,
+      "num_tokens": 1171363.0,
+      "step": 69
+    },
+    {
+      "epoch": 0.014,
+      "grad_norm": 11.756244659423828,
+      "learning_rate": 4.931e-06,
+      "loss": 12.6686,
+      "mean_token_accuracy": 0.28285714983940125,
+      "num_tokens": 1185814.0,
+      "step": 70
+    },
+    {
+      "epoch": 0.0142,
+      "grad_norm": 9.128395080566406,
+      "learning_rate": 4.93e-06,
+      "loss": 11.1826,
+      "mean_token_accuracy": 0.21765056997537613,
+      "num_tokens": 1200437.0,
+      "step": 71
+    },
+    {
+      "epoch": 0.0144,
+      "grad_norm": 8.472599029541016,
+      "learning_rate": 4.929000000000001e-06,
+      "loss": 11.6617,
+      "mean_token_accuracy": 0.2060810774564743,
+      "num_tokens": 1219264.0,
+      "step": 72
+    },
+    {
+      "epoch": 0.0146,
+      "grad_norm": 11.549400329589844,
+      "learning_rate": 4.928000000000001e-06,
+      "loss": 12.9588,
+      "mean_token_accuracy": 0.25,
+      "num_tokens": 1238560.0,
+      "step": 73
+    },
+    {
+      "epoch": 0.0148,
+      "grad_norm": 11.084433555603027,
+      "learning_rate": 4.9270000000000004e-06,
+      "loss": 10.4111,
+      "mean_token_accuracy": 0.21954887360334396,
+      "num_tokens": 1247376.0,
+      "step": 74
+    },
+    {
+      "epoch": 0.015,
+      "grad_norm": 10.906563758850098,
+      "learning_rate": 4.926e-06,
+      "loss": 12.5231,
+      "mean_token_accuracy": 0.23307790607213974,
+      "num_tokens": 1266611.0,
+      "step": 75
+    },
+    {
+      "epoch": 0.0152,
+      "grad_norm": 9.466647148132324,
+      "learning_rate": 4.925e-06,
+      "loss": 11.4363,
+      "mean_token_accuracy": 0.24193547666072845,
+      "num_tokens": 1281132.0,
+      "step": 76
+    },
+    {
+      "epoch": 0.0154,
+      "grad_norm": 11.185935020446777,
+      "learning_rate": 4.924000000000001e-06,
+      "loss": 12.6383,
+      "mean_token_accuracy": 0.22685185074806213,
+      "num_tokens": 1301049.0,
+      "step": 77
+    },
+    {
+      "epoch": 0.0156,
+      "grad_norm": 11.0143461227417,
+      "learning_rate": 4.923000000000001e-06,
+      "loss": 12.479,
+      "mean_token_accuracy": 0.22962962836027145,
+      "num_tokens": 1322278.0,
+      "step": 78
+    },
+    {
+      "epoch": 0.0158,
+      "grad_norm": 12.330080032348633,
+      "learning_rate": 4.9220000000000005e-06,
+      "loss": 12.2351,
+      "mean_token_accuracy": 0.2675606608390808,
+      "num_tokens": 1341536.0,
+      "step": 79
+    },
+    {
+      "epoch": 0.016,
+      "grad_norm": 10.486513137817383,
+      "learning_rate": 4.921e-06,
+      "loss": 11.6896,
+      "mean_token_accuracy": 0.25356507301330566,
+      "num_tokens": 1355885.0,
+      "step": 80
+    },
+    {
+      "epoch": 0.0162,
+      "grad_norm": 12.150262832641602,
+      "learning_rate": 4.92e-06,
+      "loss": 12.5725,
+      "mean_token_accuracy": 0.2321428582072258,
+      "num_tokens": 1375181.0,
+      "step": 81
+    },
+    {
+      "epoch": 0.0164,
+      "grad_norm": 11.387964248657227,
+      "learning_rate": 4.919000000000001e-06,
+      "loss": 11.5796,
+      "mean_token_accuracy": 0.29461538791656494,
+      "num_tokens": 1384853.0,
+      "step": 82
+    },
+    {
+      "epoch": 0.0166,
+      "grad_norm": 9.878727912902832,
+      "learning_rate": 4.918e-06,
+      "loss": 11.7534,
+      "mean_token_accuracy": 0.24473684281110764,
+      "num_tokens": 1401178.0,
+      "step": 83
+    },
+    {
+      "epoch": 0.0168,
+      "grad_norm": 9.827662467956543,
+      "learning_rate": 4.9170000000000005e-06,
+      "loss": 12.0345,
+      "mean_token_accuracy": 0.18034055829048157,
+      "num_tokens": 1419976.0,
+      "step": 84
+    },
+    {
+      "epoch": 0.017,
+      "grad_norm": 10.327628135681152,
+      "learning_rate": 4.916e-06,
+      "loss": 11.1049,
+      "mean_token_accuracy": 0.3095238208770752,
+      "num_tokens": 1429652.0,
+      "step": 85
+    },
+    {
+      "epoch": 0.0172,
+      "grad_norm": 10.67590045928955,
+      "learning_rate": 4.915e-06,
+      "loss": 10.7087,
+      "mean_token_accuracy": 0.2750582844018936,
+      "num_tokens": 1444113.0,
+      "step": 86
+    },
+    {
+      "epoch": 0.0174,
+      "grad_norm": 20.292959213256836,
+      "learning_rate": 4.914000000000001e-06,
+      "loss": 10.797,
+      "mean_token_accuracy": 0.32500000298023224,
+      "num_tokens": 1453773.0,
+      "step": 87
+    },
+    {
+      "epoch": 0.0176,
+      "grad_norm": 8.3117036819458,
+      "learning_rate": 4.913e-06,
+      "loss": 9.394,
+      "mean_token_accuracy": 0.31915584206581116,
+      "num_tokens": 1475024.0,
+      "step": 88
+    },
+    {
+      "epoch": 0.0178,
+      "grad_norm": 11.334404945373535,
+      "learning_rate": 4.9120000000000006e-06,
+      "loss": 11.0718,
+      "mean_token_accuracy": 0.2678571492433548,
+      "num_tokens": 1489489.0,
+      "step": 89
+    },
+    {
+      "epoch": 0.018,
+      "grad_norm": 15.36023235321045,
+      "learning_rate": 4.911e-06,
+      "loss": 11.7992,
+      "mean_token_accuracy": 0.28607918322086334,
+      "num_tokens": 1508816.0,
+      "step": 90
+    },
+    {
+      "epoch": 0.0182,
+      "grad_norm": 11.725635528564453,
+      "learning_rate": 4.9100000000000004e-06,
+      "loss": 11.9207,
+      "mean_token_accuracy": 0.26123301684856415,
+      "num_tokens": 1530050.0,
+      "step": 91
+    },
+    {
+      "epoch": 0.0184,
+      "grad_norm": 14.75428295135498,
+      "learning_rate": 4.909000000000001e-06,
+      "loss": 11.0294,
+      "mean_token_accuracy": 0.21236559003591537,
+      "num_tokens": 1544713.0,
+      "step": 92
+    },
+    {
+      "epoch": 0.0186,
+      "grad_norm": 10.447436332702637,
+      "learning_rate": 4.908e-06,
+      "loss": 9.7536,
+      "mean_token_accuracy": 0.24568965286016464,
+      "num_tokens": 1559226.0,
+      "step": 93
+    },
+    {
+      "epoch": 0.0188,
+      "grad_norm": 14.036280632019043,
+      "learning_rate": 4.907000000000001e-06,
+      "loss": 12.2065,
+      "mean_token_accuracy": 0.2771739065647125,
+      "num_tokens": 1568898.0,
+      "step": 94
+    },
+    {
+      "epoch": 0.019,
+      "grad_norm": 13.364744186401367,
+      "learning_rate": 4.906e-06,
+      "loss": 13.168,
+      "mean_token_accuracy": 0.2321428582072258,
+      "num_tokens": 1588133.0,
+      "step": 95
+    },
+    {
+      "epoch": 0.0192,
+      "grad_norm": 12.441611289978027,
+      "learning_rate": 4.9050000000000005e-06,
+      "loss": 11.6806,
+      "mean_token_accuracy": 0.21875,
+      "num_tokens": 1607218.0,
+      "step": 96
+    },
+    {
+      "epoch": 0.0194,
+      "grad_norm": 11.559666633605957,
+      "learning_rate": 4.904000000000001e-06,
+      "loss": 12.2055,
+      "mean_token_accuracy": 0.23010753095149994,
+      "num_tokens": 1626557.0,
+      "step": 97
+    },
+    {
+      "epoch": 0.0196,
+      "grad_norm": 11.131147384643555,
+      "learning_rate": 4.903e-06,
+      "loss": 11.4201,
+      "mean_token_accuracy": 0.2931034490466118,
+      "num_tokens": 1641017.0,
+      "step": 98
+    },
+    {
+      "epoch": 0.0198,
+      "grad_norm": 12.186894416809082,
+      "learning_rate": 4.902000000000001e-06,
+      "loss": 12.1568,
+      "mean_token_accuracy": 0.23180076479911804,
+      "num_tokens": 1655475.0,
+      "step": 99
+    },
+    {
+      "epoch": 0.02,
+      "grad_norm": 11.864778518676758,
+      "learning_rate": 4.901e-06,
+      "loss": 12.4851,
+      "mean_token_accuracy": 0.21008403599262238,
+      "num_tokens": 1674815.0,
+      "step": 100
+    },
+    {
+      "epoch": 0.0202,
+      "grad_norm": 14.35185718536377,
+      "learning_rate": 4.9000000000000005e-06,
+      "loss": 11.1814,
+      "mean_token_accuracy": 0.2612612694501877,
+      "num_tokens": 1686681.0,
+      "step": 101
+    },
+    {
+      "epoch": 0.0204,
+      "grad_norm": 18.715627670288086,
+      "learning_rate": 4.899e-06,
+      "loss": 11.632,
+      "mean_token_accuracy": 0.30199430882930756,
+      "num_tokens": 1701565.0,
+      "step": 102
+    },
+    {
+      "epoch": 0.0206,
+      "grad_norm": 12.892010688781738,
+      "learning_rate": 4.898e-06,
+      "loss": 12.3157,
+      "mean_token_accuracy": 0.23806367069482803,
+      "num_tokens": 1715938.0,
+      "step": 103
+    },
+    {
+      "epoch": 0.0208,
+      "grad_norm": 13.078173637390137,
+      "learning_rate": 4.897000000000001e-06,
+      "loss": 11.4954,
+      "mean_token_accuracy": 0.22177419066429138,
+      "num_tokens": 1734685.0,
+      "step": 104
+    },
+    {
+      "epoch": 0.021,
+      "grad_norm": 14.580618858337402,
+      "learning_rate": 4.896e-06,
+      "loss": 10.4619,
+      "mean_token_accuracy": 0.2797202914953232,
+      "num_tokens": 1757899.0,
+      "step": 105
+    },
+    {
+      "epoch": 0.0212,
+      "grad_norm": 13.174345016479492,
+      "learning_rate": 4.8950000000000006e-06,
+      "loss": 10.5835,
+      "mean_token_accuracy": 0.27546295523643494,
+      "num_tokens": 1778410.0,
+      "step": 106
+    },
+    {
+      "epoch": 0.0214,
+      "grad_norm": 13.970446586608887,
+      "learning_rate": 4.894e-06,
+      "loss": 11.1265,
+      "mean_token_accuracy": 0.2693749964237213,
+      "num_tokens": 1791819.0,
+      "step": 107
+    },
+    {
+      "epoch": 0.0216,
+      "grad_norm": 11.994514465332031,
+      "learning_rate": 4.893e-06,
+      "loss": 11.3511,
+      "mean_token_accuracy": 0.25462962687015533,
+      "num_tokens": 1811118.0,
+      "step": 108
+    },
+    {
+      "epoch": 0.0218,
+      "grad_norm": 13.328775405883789,
+      "learning_rate": 4.892000000000001e-06,
+      "loss": 11.9787,
+      "mean_token_accuracy": 0.23790322244167328,
+      "num_tokens": 1825598.0,
+      "step": 109
+    },
+    {
+      "epoch": 0.022,
+      "grad_norm": 11.813949584960938,
+      "learning_rate": 4.891e-06,
+      "loss": 10.614,
+      "mean_token_accuracy": 0.25833334028720856,
+      "num_tokens": 1840096.0,
+      "step": 110
+    },
+    {
+      "epoch": 0.0222,
+      "grad_norm": 17.409263610839844,
+      "learning_rate": 4.890000000000001e-06,
+      "loss": 10.5087,
+      "mean_token_accuracy": 0.32692308723926544,
+      "num_tokens": 1849750.0,
+      "step": 111
+    },
+    {
+      "epoch": 0.0224,
+      "grad_norm": 19.462722778320312,
+      "learning_rate": 4.889e-06,
+      "loss": 10.2288,
+      "mean_token_accuracy": 0.25729166716337204,
+      "num_tokens": 1859433.0,
+      "step": 112
+    },
+    {
+      "epoch": 0.0226,
+      "grad_norm": 11.595419883728027,
+      "learning_rate": 4.8880000000000005e-06,
+      "loss": 11.0996,
+      "mean_token_accuracy": 0.2807881832122803,
+      "num_tokens": 1873892.0,
+      "step": 113
+    },
+    {
+      "epoch": 0.0228,
+      "grad_norm": 14.413046836853027,
+      "learning_rate": 4.887000000000001e-06,
+      "loss": 11.6535,
+      "mean_token_accuracy": 0.2341153472661972,
+      "num_tokens": 1893196.0,
+      "step": 114
+    },
+    {
+      "epoch": 0.023,
+      "grad_norm": 12.218829154968262,
+      "learning_rate": 4.886e-06,
+      "loss": 10.9169,
+      "mean_token_accuracy": 0.2557603716850281,
+      "num_tokens": 1907676.0,
+      "step": 115
+    },
+    {
+      "epoch": 0.0232,
+      "grad_norm": 16.51720428466797,
+      "learning_rate": 4.885000000000001e-06,
+      "loss": 9.8406,
+      "mean_token_accuracy": 0.25968992710113525,
+      "num_tokens": 1921596.0,
+      "step": 116
+    },
+    {
+      "epoch": 0.0234,
+      "grad_norm": 10.608232498168945,
+      "learning_rate": 4.884e-06,
+      "loss": 9.9809,
+      "mean_token_accuracy": 0.22068965435028076,
+      "num_tokens": 1940247.0,
+      "step": 117
+    },
+    {
+      "epoch": 0.0236,
+      "grad_norm": 14.17568302154541,
+      "learning_rate": 4.8830000000000005e-06,
+      "loss": 11.3908,
+      "mean_token_accuracy": 0.23790322244167328,
+      "num_tokens": 1959268.0,
+      "step": 118
+    },
+    {
+      "epoch": 0.0238,
+      "grad_norm": 12.197131156921387,
+      "learning_rate": 4.882000000000001e-06,
+      "loss": 10.9438,
+      "mean_token_accuracy": 0.2538699731230736,
+      "num_tokens": 1978218.0,
+      "step": 119
+    },
+    {
+      "epoch": 0.024,
+      "grad_norm": 15.261062622070312,
+      "learning_rate": 4.881e-06,
+      "loss": 11.0329,
+      "mean_token_accuracy": 0.24621212482452393,
+      "num_tokens": 1997519.0,
+      "step": 120
+    },
+    {
+      "epoch": 0.0242,
+      "grad_norm": 13.116536140441895,
+      "learning_rate": 4.880000000000001e-06,
+      "loss": 11.9918,
+      "mean_token_accuracy": 0.24137930572032928,
+      "num_tokens": 2016817.0,
+      "step": 121
+    },
+    {
+      "epoch": 0.0244,
+      "grad_norm": 18.174373626708984,
+      "learning_rate": 4.879e-06,
+      "loss": 11.0414,
+      "mean_token_accuracy": 0.25833334028720856,
+      "num_tokens": 2035875.0,
+      "step": 122
+    },
+    {
+      "epoch": 0.0246,
+      "grad_norm": 17.258121490478516,
+      "learning_rate": 4.8780000000000006e-06,
+      "loss": 11.1173,
+      "mean_token_accuracy": 0.3010057359933853,
+      "num_tokens": 2050330.0,
+      "step": 123
+    },
+    {
+      "epoch": 0.0248,
+      "grad_norm": 12.636884689331055,
+      "learning_rate": 4.877000000000001e-06,
+      "loss": 11.3399,
+      "mean_token_accuracy": 0.2879464328289032,
+      "num_tokens": 2070156.0,
+      "step": 124
+    },
+    {
+      "epoch": 0.025,
+      "grad_norm": 18.457618713378906,
+      "learning_rate": 4.876e-06,
+      "loss": 11.5595,
+      "mean_token_accuracy": 0.28418803960084915,
+      "num_tokens": 2084771.0,
+      "step": 125
+    },
+    {
+      "epoch": 0.0252,
+      "grad_norm": 14.281397819519043,
+      "learning_rate": 4.875e-06,
+      "loss": 10.9901,
+      "mean_token_accuracy": 0.28140393644571304,
+      "num_tokens": 2104228.0,
+      "step": 126
+    },
+    {
+      "epoch": 0.0254,
+      "grad_norm": 13.08484935760498,
+      "learning_rate": 4.874e-06,
+      "loss": 9.4802,
+      "mean_token_accuracy": 0.2637759745121002,
+      "num_tokens": 2118877.0,
+      "step": 127
+    },
+    {
+      "epoch": 0.0256,
+      "grad_norm": 11.949925422668457,
+      "learning_rate": 4.873000000000001e-06,
+      "loss": 10.3703,
+      "mean_token_accuracy": 0.2619825750589371,
+      "num_tokens": 2133298.0,
+      "step": 128
+    },
+    {
+      "epoch": 0.0258,
+      "grad_norm": 14.950297355651855,
+      "learning_rate": 4.872000000000001e-06,
+      "loss": 10.6116,
+      "mean_token_accuracy": 0.33000001311302185,
+      "num_tokens": 2142955.0,
+      "step": 129
+    },
+    {
+      "epoch": 0.026,
+      "grad_norm": 16.433286666870117,
+      "learning_rate": 4.8710000000000005e-06,
+      "loss": 9.4482,
+      "mean_token_accuracy": 0.3333333432674408,
+      "num_tokens": 2159447.0,
+      "step": 130
+    },
+    {
+      "epoch": 0.0262,
+      "grad_norm": 12.467981338500977,
+      "learning_rate": 4.87e-06,
+      "loss": 10.2354,
+      "mean_token_accuracy": 0.33796295523643494,
+      "num_tokens": 2178352.0,
+      "step": 131
+    },
+    {
+      "epoch": 0.0264,
+      "grad_norm": 11.493000030517578,
+      "learning_rate": 4.869e-06,
+      "loss": 9.0597,
+      "mean_token_accuracy": 0.2736175060272217,
+      "num_tokens": 2199174.0,
+      "step": 132
+    },
+    {
+      "epoch": 0.0266,
+      "grad_norm": 13.966115951538086,
+      "learning_rate": 4.868000000000001e-06,
+      "loss": 10.3177,
+      "mean_token_accuracy": 0.3325917571783066,
+      "num_tokens": 2213636.0,
+      "step": 133
+    },
+    {
+      "epoch": 0.0268,
+      "grad_norm": 13.971321105957031,
+      "learning_rate": 4.867000000000001e-06,
+      "loss": 10.2564,
+      "mean_token_accuracy": 0.31481482088565826,
+      "num_tokens": 2228050.0,
+      "step": 134
+    },
+    {
+      "epoch": 0.027,
+      "grad_norm": 16.246124267578125,
+      "learning_rate": 4.8660000000000005e-06,
+      "loss": 10.7549,
+      "mean_token_accuracy": 0.30943846702575684,
+      "num_tokens": 2247348.0,
+      "step": 135
+    },
+    {
+      "epoch": 0.0272,
+      "grad_norm": 17.702425003051758,
+      "learning_rate": 4.865e-06,
+      "loss": 10.1729,
+      "mean_token_accuracy": 0.3575989753007889,
+      "num_tokens": 2261806.0,
+      "step": 136
+    },
+    {
+      "epoch": 0.0274,
+      "grad_norm": 13.732104301452637,
+      "learning_rate": 4.864e-06,
+      "loss": 10.9004,
+      "mean_token_accuracy": 0.28607918322086334,
+      "num_tokens": 2281224.0,
+      "step": 137
+    },
+    {
+      "epoch": 0.0276,
+      "grad_norm": 17.568925857543945,
+      "learning_rate": 4.863000000000001e-06,
+      "loss": 10.1658,
+      "mean_token_accuracy": 0.2857142984867096,
+      "num_tokens": 2295720.0,
+      "step": 138
+    },
+    {
+      "epoch": 0.0278,
+      "grad_norm": 13.424271583557129,
+      "learning_rate": 4.862e-06,
+      "loss": 10.3543,
+      "mean_token_accuracy": 0.28928571939468384,
+      "num_tokens": 2310345.0,
+      "step": 139
+    },
+    {
+      "epoch": 0.028,
+      "grad_norm": 14.413524627685547,
+      "learning_rate": 4.8610000000000006e-06,
+      "loss": 11.3822,
+      "mean_token_accuracy": 0.22828783839941025,
+      "num_tokens": 2347736.0,
+      "step": 140
+    },
+    {
+      "epoch": 0.0282,
+      "grad_norm": 22.185630798339844,
+      "learning_rate": 4.86e-06,
+      "loss": 10.6185,
+      "mean_token_accuracy": 0.2911111190915108,
+      "num_tokens": 2361685.0,
+      "step": 141
+    },
+    {
+      "epoch": 0.0284,
+      "grad_norm": 12.253998756408691,
+      "learning_rate": 4.859e-06,
+      "loss": 9.2399,
+      "mean_token_accuracy": 0.288621261715889,
+      "num_tokens": 2376158.0,
+      "step": 142
+    },
+    {
+      "epoch": 0.0286,
+      "grad_norm": 16.229686737060547,
+      "learning_rate": 4.858000000000001e-06,
+      "loss": 10.3377,
+      "mean_token_accuracy": 0.22227822244167328,
+      "num_tokens": 2391501.0,
+      "step": 143
+    },
+    {
+      "epoch": 0.0288,
+      "grad_norm": 9.664397239685059,
+      "learning_rate": 4.857e-06,
+      "loss": 9.3351,
+      "mean_token_accuracy": 0.26456456631422043,
+      "num_tokens": 2411105.0,
+      "step": 144
+    },
+    {
+      "epoch": 0.029,
+      "grad_norm": 12.8119478225708,
+      "learning_rate": 4.856e-06,
+      "loss": 9.87,
+      "mean_token_accuracy": 0.24166666716337204,
+      "num_tokens": 2431185.0,
+      "step": 145
+    },
+    {
+      "epoch": 0.0292,
+      "grad_norm": 10.490764617919922,
+      "learning_rate": 4.855e-06,
+      "loss": 8.7889,
+      "mean_token_accuracy": 0.36666667461395264,
+      "num_tokens": 2452470.0,
+      "step": 146
+    },
+    {
+      "epoch": 0.0294,
+      "grad_norm": 13.65211296081543,
+      "learning_rate": 4.8540000000000005e-06,
+      "loss": 10.4286,
+      "mean_token_accuracy": 0.2718253955245018,
+      "num_tokens": 2472396.0,
+      "step": 147
+    },
+    {
+      "epoch": 0.0296,
+      "grad_norm": 18.866209030151367,
+      "learning_rate": 4.853000000000001e-06,
+      "loss": 10.2372,
+      "mean_token_accuracy": 0.38141025602817535,
+      "num_tokens": 2486886.0,
+      "step": 148
+    },
+    {
+      "epoch": 0.0298,
+      "grad_norm": 14.852785110473633,
+      "learning_rate": 4.852e-06,
+      "loss": 10.0487,
+      "mean_token_accuracy": 0.30820105969905853,
+      "num_tokens": 2506143.0,
+      "step": 149
+    },
+    {
+      "epoch": 0.03,
+      "grad_norm": 13.972378730773926,
+      "learning_rate": 4.851e-06,
+      "loss": 10.6291,
+      "mean_token_accuracy": 0.25820106267929077,
+      "num_tokens": 2520401.0,
+      "step": 150
+    },
+    {
+      "epoch": 0.0302,
+      "grad_norm": 14.618459701538086,
+      "learning_rate": 4.85e-06,
+      "loss": 10.7579,
+      "mean_token_accuracy": 0.23571428656578064,
+      "num_tokens": 2539135.0,
+      "step": 151
+    },
+    {
+      "epoch": 0.0304,
+      "grad_norm": 15.176739692687988,
+      "learning_rate": 4.8490000000000005e-06,
+      "loss": 9.6595,
+      "mean_token_accuracy": 0.2510339096188545,
+      "num_tokens": 2558562.0,
+      "step": 152
+    },
+    {
+      "epoch": 0.0306,
+      "grad_norm": 16.972919464111328,
+      "learning_rate": 4.848000000000001e-06,
+      "loss": 10.8999,
+      "mean_token_accuracy": 0.25925925374031067,
+      "num_tokens": 2577856.0,
+      "step": 153
+    },
+    {
+      "epoch": 0.0308,
+      "grad_norm": 16.451147079467773,
+      "learning_rate": 4.847e-06,
+      "loss": 8.5505,
+      "mean_token_accuracy": 0.36249999701976776,
+      "num_tokens": 2592246.0,
+      "step": 154
+    },
+    {
+      "epoch": 0.031,
+      "grad_norm": 24.95278549194336,
+      "learning_rate": 4.846e-06,
+      "loss": 10.2367,
+      "mean_token_accuracy": 0.28735632449388504,
+      "num_tokens": 2607133.0,
+      "step": 155
+    },
+    {
+      "epoch": 0.0312,
+      "grad_norm": 15.770346641540527,
+      "learning_rate": 4.845e-06,
+      "loss": 9.6085,
+      "mean_token_accuracy": 0.27272728085517883,
+      "num_tokens": 2621734.0,
+      "step": 156
+    },
+    {
+      "epoch": 0.0314,
+      "grad_norm": 12.314064025878906,
+      "learning_rate": 4.8440000000000005e-06,
+      "loss": 9.816,
+      "mean_token_accuracy": 0.2540322542190552,
+      "num_tokens": 2641357.0,
+      "step": 157
+    },
+    {
+      "epoch": 0.0316,
+      "grad_norm": 13.379799842834473,
+      "learning_rate": 4.843000000000001e-06,
+      "loss": 10.378,
+      "mean_token_accuracy": 0.32804232835769653,
+      "num_tokens": 2660177.0,
+      "step": 158
+    },
+    {
+      "epoch": 0.0318,
+      "grad_norm": 17.458240509033203,
+      "learning_rate": 4.842e-06,
+      "loss": 9.3842,
+      "mean_token_accuracy": 0.2557164579629898,
+      "num_tokens": 2679528.0,
+      "step": 159
+    },
+    {
+      "epoch": 0.032,
+      "grad_norm": 25.741785049438477,
+      "learning_rate": 4.841e-06,
+      "loss": 9.0768,
+      "mean_token_accuracy": 0.3270474076271057,
+      "num_tokens": 2693652.0,
+      "step": 160
+    },
+    {
+      "epoch": 0.0322,
+      "grad_norm": 13.557204246520996,
+      "learning_rate": 4.84e-06,
+      "loss": 9.6471,
+      "mean_token_accuracy": 0.28735632449388504,
+      "num_tokens": 2713320.0,
+      "step": 161
+    },
+    {
+      "epoch": 0.0324,
+      "grad_norm": 14.830061912536621,
+      "learning_rate": 4.839000000000001e-06,
+      "loss": 11.3496,
+      "mean_token_accuracy": 0.24049513787031174,
+      "num_tokens": 2733424.0,
+      "step": 162
+    },
+    {
+      "epoch": 0.0326,
+      "grad_norm": 12.371265411376953,
+      "learning_rate": 4.838e-06,
+      "loss": 8.6217,
+      "mean_token_accuracy": 0.25988225638866425,
+      "num_tokens": 2752613.0,
+      "step": 163
+    },
+    {
+      "epoch": 0.0328,
+      "grad_norm": 12.722640037536621,
+      "learning_rate": 4.8370000000000004e-06,
+      "loss": 9.2979,
+      "mean_token_accuracy": 0.2337121218442917,
+      "num_tokens": 2773896.0,
+      "step": 164
+    },
+    {
+      "epoch": 0.033,
+      "grad_norm": 12.796667098999023,
+      "learning_rate": 4.836e-06,
+      "loss": 9.9112,
+      "mean_token_accuracy": 0.3337438404560089,
+      "num_tokens": 2793334.0,
+      "step": 165
+    },
+    {
+      "epoch": 0.0332,
+      "grad_norm": 15.983271598815918,
+      "learning_rate": 4.835e-06,
+      "loss": 9.5066,
+      "mean_token_accuracy": 0.29256465286016464,
+      "num_tokens": 2807755.0,
+      "step": 166
+    },
+    {
+      "epoch": 0.0334,
+      "grad_norm": 15.554715156555176,
+      "learning_rate": 4.834000000000001e-06,
+      "loss": 10.5127,
+      "mean_token_accuracy": 0.2986453175544739,
+      "num_tokens": 2827193.0,
+      "step": 167
+    },
+    {
+      "epoch": 0.0336,
+      "grad_norm": 14.6381196975708,
+      "learning_rate": 4.833e-06,
+      "loss": 9.7383,
+      "mean_token_accuracy": 0.2586618810892105,
+      "num_tokens": 2846449.0,
+      "step": 168
+    },
+    {
+      "epoch": 0.0338,
+      "grad_norm": 16.013647079467773,
+      "learning_rate": 4.8320000000000005e-06,
+      "loss": 9.0009,
+      "mean_token_accuracy": 0.32356322556734085,
+      "num_tokens": 2860910.0,
+      "step": 169
+    },
+    {
+      "epoch": 0.034,
+      "grad_norm": 13.708538055419922,
+      "learning_rate": 4.831e-06,
+      "loss": 9.4298,
+      "mean_token_accuracy": 0.28114478290081024,
+      "num_tokens": 2880172.0,
+      "step": 170
+    },
+    {
+      "epoch": 0.0342,
+      "grad_norm": 14.314607620239258,
+      "learning_rate": 4.83e-06,
+      "loss": 9.2596,
+      "mean_token_accuracy": 0.3014460504055023,
+      "num_tokens": 2899434.0,
+      "step": 171
+    },
+    {
+      "epoch": 0.0344,
+      "grad_norm": 12.27084732055664,
+      "learning_rate": 4.829000000000001e-06,
+      "loss": 9.5638,
+      "mean_token_accuracy": 0.33095238357782364,
+      "num_tokens": 2913932.0,
+      "step": 172
+    },
+    {
+      "epoch": 0.0346,
+      "grad_norm": 14.023222923278809,
+      "learning_rate": 4.828e-06,
+      "loss": 9.689,
+      "mean_token_accuracy": 0.31680162250995636,
+      "num_tokens": 2928356.0,
+      "step": 173
+    },
+    {
+      "epoch": 0.0348,
+      "grad_norm": 14.490949630737305,
+      "learning_rate": 4.8270000000000005e-06,
+      "loss": 8.8018,
+      "mean_token_accuracy": 0.34068627655506134,
+      "num_tokens": 2940589.0,
+      "step": 174
+    },
+    {
+      "epoch": 0.035,
+      "grad_norm": 17.97809410095215,
+      "learning_rate": 4.826e-06,
+      "loss": 9.9556,
+      "mean_token_accuracy": 0.3452381044626236,
+      "num_tokens": 2959486.0,
+      "step": 175
+    },
+    {
+      "epoch": 0.0352,
+      "grad_norm": 13.302875518798828,
+      "learning_rate": 4.825e-06,
+      "loss": 9.4104,
+      "mean_token_accuracy": 0.23885918408632278,
+      "num_tokens": 2974195.0,
+      "step": 176
+    },
+    {
+      "epoch": 0.0354,
+      "grad_norm": 12.792606353759766,
+      "learning_rate": 4.824000000000001e-06,
+      "loss": 8.2518,
+      "mean_token_accuracy": 0.42592592537403107,
+      "num_tokens": 2984011.0,
+      "step": 177
+    },
+    {
+      "epoch": 0.0356,
+      "grad_norm": 18.23525619506836,
+      "learning_rate": 4.823e-06,
+      "loss": 8.8069,
+      "mean_token_accuracy": 0.40079365670681,
+      "num_tokens": 2998487.0,
+      "step": 178
+    },
+    {
+      "epoch": 0.0358,
+      "grad_norm": 14.206355094909668,
+      "learning_rate": 4.822000000000001e-06,
+      "loss": 9.1892,
+      "mean_token_accuracy": 0.2290322557091713,
+      "num_tokens": 3019773.0,
+      "step": 179
+    },
+    {
+      "epoch": 0.036,
+      "grad_norm": 12.26903247833252,
+      "learning_rate": 4.821e-06,
+      "loss": 8.4939,
+      "mean_token_accuracy": 0.28287841379642487,
+      "num_tokens": 3040775.0,
+      "step": 180
+    },
+    {
+      "epoch": 0.0362,
+      "grad_norm": 15.23544979095459,
+      "learning_rate": 4.8200000000000004e-06,
+      "loss": 8.9121,
+      "mean_token_accuracy": 0.3285440653562546,
+      "num_tokens": 3060080.0,
+      "step": 181
+    },
+    {
+      "epoch": 0.0364,
+      "grad_norm": 57.132049560546875,
+      "learning_rate": 4.819e-06,
+      "loss": 8.9738,
+      "mean_token_accuracy": 0.3175750821828842,
+      "num_tokens": 3079332.0,
+      "step": 182
+    },
+    {
+      "epoch": 0.0366,
+      "grad_norm": 13.691211700439453,
+      "learning_rate": 4.818e-06,
+      "loss": 8.0025,
+      "mean_token_accuracy": 0.34656085073947906,
+      "num_tokens": 3088989.0,
+      "step": 183
+    },
+    {
+      "epoch": 0.0368,
+      "grad_norm": 15.762035369873047,
+      "learning_rate": 4.817000000000001e-06,
+      "loss": 9.4602,
+      "mean_token_accuracy": 0.34457671642303467,
+      "num_tokens": 3107732.0,
+      "step": 184
+    },
+    {
+      "epoch": 0.037,
+      "grad_norm": 17.034019470214844,
+      "learning_rate": 4.816e-06,
+      "loss": 9.4491,
+      "mean_token_accuracy": 0.34666667878627777,
+      "num_tokens": 3122423.0,
+      "step": 185
+    },
+    {
+      "epoch": 0.0372,
+      "grad_norm": 12.461385726928711,
+      "learning_rate": 4.8150000000000005e-06,
+      "loss": 9.0659,
+      "mean_token_accuracy": 0.2838345915079117,
+      "num_tokens": 3141889.0,
+      "step": 186
+    },
+    {
+      "epoch": 0.0374,
+      "grad_norm": 13.194416046142578,
+      "learning_rate": 4.814e-06,
+      "loss": 8.8107,
+      "mean_token_accuracy": 0.36685824394226074,
+      "num_tokens": 3161194.0,
+      "step": 187
+    },
+    {
+      "epoch": 0.0376,
+      "grad_norm": 14.799727439880371,
+      "learning_rate": 4.813e-06,
+      "loss": 9.7196,
+      "mean_token_accuracy": 0.377616748213768,
+      "num_tokens": 3175646.0,
+      "step": 188
+    },
+    {
+      "epoch": 0.0378,
+      "grad_norm": 15.303200721740723,
+      "learning_rate": 4.812000000000001e-06,
+      "loss": 10.0029,
+      "mean_token_accuracy": 0.38161374628543854,
+      "num_tokens": 3194941.0,
+      "step": 189
+    },
+    {
+      "epoch": 0.038,
+      "grad_norm": 13.99432373046875,
+      "learning_rate": 4.811000000000001e-06,
+      "loss": 8.4004,
+      "mean_token_accuracy": 0.37096773087978363,
+      "num_tokens": 3214205.0,
+      "step": 190
+    },
+    {
+      "epoch": 0.0382,
+      "grad_norm": 12.163537979125977,
+      "learning_rate": 4.8100000000000005e-06,
+      "loss": 9.0058,
+      "mean_token_accuracy": 0.35395538806915283,
+      "num_tokens": 3235063.0,
+      "step": 191
+    },
+    {
+      "epoch": 0.0384,
+      "grad_norm": 12.369959831237793,
+      "learning_rate": 4.809e-06,
+      "loss": 9.0358,
+      "mean_token_accuracy": 0.4807407408952713,
+      "num_tokens": 3249517.0,
+      "step": 192
+    },
+    {
+      "epoch": 0.0386,
+      "grad_norm": 21.97284698486328,
+      "learning_rate": 4.808e-06,
+      "loss": 8.7725,
+      "mean_token_accuracy": 0.41179338097572327,
+      "num_tokens": 3268738.0,
+      "step": 193
+    },
+    {
+      "epoch": 0.0388,
+      "grad_norm": 13.040814399719238,
+      "learning_rate": 4.807000000000001e-06,
+      "loss": 9.4628,
+      "mean_token_accuracy": 0.424450546503067,
+      "num_tokens": 3288032.0,
+      "step": 194
+    },
+    {
+      "epoch": 0.039,
+      "grad_norm": 14.395992279052734,
+      "learning_rate": 4.806000000000001e-06,
+      "loss": 9.1626,
+      "mean_token_accuracy": 0.454365074634552,
+      "num_tokens": 3306813.0,
+      "step": 195
+    },
+    {
+      "epoch": 0.0392,
+      "grad_norm": 11.64809799194336,
+      "learning_rate": 4.805000000000001e-06,
+      "loss": 8.7527,
+      "mean_token_accuracy": 0.3843159079551697,
+      "num_tokens": 3325561.0,
+      "step": 196
+    },
+    {
+      "epoch": 0.0394,
+      "grad_norm": 25.551607131958008,
+      "learning_rate": 4.804e-06,
+      "loss": 8.5253,
+      "mean_token_accuracy": 0.3452381044626236,
+      "num_tokens": 3339397.0,
+      "step": 197
+    },
+    {
+      "epoch": 0.0396,
+      "grad_norm": 12.025030136108398,
+      "learning_rate": 4.8030000000000004e-06,
+      "loss": 7.7581,
+      "mean_token_accuracy": 0.5191570967435837,
+      "num_tokens": 3349055.0,
+      "step": 198
+    },
+    {
+      "epoch": 0.0398,
+      "grad_norm": 10.044900894165039,
+      "learning_rate": 4.802000000000001e-06,
+      "loss": 9.0733,
+      "mean_token_accuracy": 0.4278416335582733,
+      "num_tokens": 3368313.0,
+      "step": 199
+    },
+    {
+      "epoch": 0.04,
+      "grad_norm": 10.911112785339355,
+      "learning_rate": 4.801e-06,
+      "loss": 8.6906,
+      "mean_token_accuracy": 0.5000000149011612,
+      "num_tokens": 3383810.0,
+      "step": 200
+    },
+    {
+      "epoch": 0.0402,
+      "grad_norm": 10.119377136230469,
+      "learning_rate": 4.800000000000001e-06,
+      "loss": 8.8941,
+      "mean_token_accuracy": 0.4000000059604645,
+      "num_tokens": 3398244.0,
+      "step": 201
+    },
+    {
+      "epoch": 0.0404,
+      "grad_norm": 10.526436805725098,
+      "learning_rate": 4.799e-06,
+      "loss": 7.8408,
+      "mean_token_accuracy": 0.39772726595401764,
+      "num_tokens": 3414686.0,
+      "step": 202
+    },
+    {
+      "epoch": 0.0406,
+      "grad_norm": 10.947959899902344,
+      "learning_rate": 4.7980000000000005e-06,
+      "loss": 8.4085,
+      "mean_token_accuracy": 0.40992647409439087,
+      "num_tokens": 3433954.0,
+      "step": 203
+    },
+    {
+      "epoch": 0.0408,
+      "grad_norm": 10.811299324035645,
+      "learning_rate": 4.797000000000001e-06,
+      "loss": 7.7418,
+      "mean_token_accuracy": 0.5370370447635651,
+      "num_tokens": 3443610.0,
+      "step": 204
+    },
+    {
+      "epoch": 0.041,
+      "grad_norm": 9.57394027709961,
+      "learning_rate": 4.796e-06,
+      "loss": 8.6595,
+      "mean_token_accuracy": 0.45967741310596466,
+      "num_tokens": 3462909.0,
+      "step": 205
+    },
+    {
+      "epoch": 0.0412,
+      "grad_norm": 12.8336181640625,
+      "learning_rate": 4.795e-06,
+      "loss": 8.6943,
+      "mean_token_accuracy": 0.45967741310596466,
+      "num_tokens": 3477620.0,
+      "step": 206
+    },
+    {
+      "epoch": 0.0414,
+      "grad_norm": 11.37842845916748,
+      "learning_rate": 4.794e-06,
+      "loss": 8.5963,
+      "mean_token_accuracy": 0.4539627134799957,
+      "num_tokens": 3496675.0,
+      "step": 207
+    },
+    {
+      "epoch": 0.0416,
+      "grad_norm": 12.427331924438477,
+      "learning_rate": 4.7930000000000005e-06,
+      "loss": 8.67,
+      "mean_token_accuracy": 0.3821548819541931,
+      "num_tokens": 3515975.0,
+      "step": 208
+    },
+    {
+      "epoch": 0.0418,
+      "grad_norm": 10.371417045593262,
+      "learning_rate": 4.792000000000001e-06,
+      "loss": 8.4859,
+      "mean_token_accuracy": 0.40784314274787903,
+      "num_tokens": 3535241.0,
+      "step": 209
+    },
+    {
+      "epoch": 0.042,
+      "grad_norm": 11.788932800292969,
+      "learning_rate": 4.791e-06,
+      "loss": 8.7143,
+      "mean_token_accuracy": 0.3741379380226135,
+      "num_tokens": 3554502.0,
+      "step": 210
+    },
+    {
+      "epoch": 0.0422,
+      "grad_norm": 15.102238655090332,
+      "learning_rate": 4.79e-06,
+      "loss": 8.5368,
+      "mean_token_accuracy": 0.40980392694473267,
+      "num_tokens": 3574437.0,
+      "step": 211
+    },
+    {
+      "epoch": 0.0424,
+      "grad_norm": 11.23690128326416,
+      "learning_rate": 4.789e-06,
+      "loss": 8.7326,
+      "mean_token_accuracy": 0.45628078281879425,
+      "num_tokens": 3593696.0,
+      "step": 212
+    },
+    {
+      "epoch": 0.0426,
+      "grad_norm": 11.3884859085083,
+      "learning_rate": 4.7880000000000006e-06,
+      "loss": 9.0773,
+      "mean_token_accuracy": 0.4404761791229248,
+      "num_tokens": 3608150.0,
+      "step": 213
+    },
+    {
+      "epoch": 0.0428,
+      "grad_norm": 11.106508255004883,
+      "learning_rate": 4.787000000000001e-06,
+      "loss": 9.5678,
+      "mean_token_accuracy": 0.3500000089406967,
+      "num_tokens": 3627724.0,
+      "step": 214
+    },
+    {
+      "epoch": 0.043,
+      "grad_norm": 11.691924095153809,
+      "learning_rate": 4.7860000000000004e-06,
+      "loss": 8.2192,
+      "mean_token_accuracy": 0.41582491993904114,
+      "num_tokens": 3642224.0,
+      "step": 215
+    },
+    {
+      "epoch": 0.0432,
+      "grad_norm": 13.973259925842285,
+      "learning_rate": 4.785e-06,
+      "loss": 8.9823,
+      "mean_token_accuracy": 0.44195401668548584,
+      "num_tokens": 3660885.0,
+      "step": 216
+    },
+    {
+      "epoch": 0.0434,
+      "grad_norm": 11.744901657104492,
+      "learning_rate": 4.784e-06,
+      "loss": 8.698,
+      "mean_token_accuracy": 0.4291125535964966,
+      "num_tokens": 3679634.0,
+      "step": 217
+    },
+    {
+      "epoch": 0.0436,
+      "grad_norm": 13.440972328186035,
+      "learning_rate": 4.783000000000001e-06,
+      "loss": 8.3414,
+      "mean_token_accuracy": 0.47999998927116394,
+      "num_tokens": 3689286.0,
+      "step": 218
+    },
+    {
+      "epoch": 0.0438,
+      "grad_norm": 9.561469078063965,
+      "learning_rate": 4.782e-06,
+      "loss": 7.6889,
+      "mean_token_accuracy": 0.41898825764656067,
+      "num_tokens": 3710533.0,
+      "step": 219
+    },
+    {
+      "epoch": 0.044,
+      "grad_norm": 12.257551193237305,
+      "learning_rate": 4.7810000000000005e-06,
+      "loss": 8.4541,
+      "mean_token_accuracy": 0.5016103088855743,
+      "num_tokens": 3725145.0,
+      "step": 220
+    },
+    {
+      "epoch": 0.0442,
+      "grad_norm": 10.785005569458008,
+      "learning_rate": 4.78e-06,
+      "loss": 9.7029,
+      "mean_token_accuracy": 0.4015151560306549,
+      "num_tokens": 3743544.0,
+      "step": 221
+    },
+    {
+      "epoch": 0.0444,
+      "grad_norm": 10.52768611907959,
+      "learning_rate": 4.779e-06,
+      "loss": 8.6062,
+      "mean_token_accuracy": 0.40740741789340973,
+      "num_tokens": 3762705.0,
+      "step": 222
+    },
+    {
+      "epoch": 0.0446,
+      "grad_norm": 17.872329711914062,
+      "learning_rate": 4.778000000000001e-06,
+      "loss": 7.3673,
+      "mean_token_accuracy": 0.45370370149612427,
+      "num_tokens": 3777166.0,
+      "step": 223
+    },
+    {
+      "epoch": 0.0448,
+      "grad_norm": 11.053666114807129,
+      "learning_rate": 4.777e-06,
+      "loss": 9.3428,
+      "mean_token_accuracy": 0.4186507910490036,
+      "num_tokens": 3795909.0,
+      "step": 224
+    },
+    {
+      "epoch": 0.045,
+      "grad_norm": 9.966497421264648,
+      "learning_rate": 4.7760000000000005e-06,
+      "loss": 7.9071,
+      "mean_token_accuracy": 0.44636015594005585,
+      "num_tokens": 3815176.0,
+      "step": 225
+    },
+    {
+      "epoch": 0.0452,
+      "grad_norm": 12.605799674987793,
+      "learning_rate": 4.775e-06,
+      "loss": 8.3063,
+      "mean_token_accuracy": 0.41692790389060974,
+      "num_tokens": 3834478.0,
+      "step": 226
+    },
+    {
+      "epoch": 0.0454,
+      "grad_norm": 9.679677963256836,
+      "learning_rate": 4.774e-06,
+      "loss": 8.7331,
+      "mean_token_accuracy": 0.45628078281879425,
+      "num_tokens": 3853737.0,
+      "step": 227
+    },
+    {
+      "epoch": 0.0456,
+      "grad_norm": 27.174549102783203,
+      "learning_rate": 4.773000000000001e-06,
+      "loss": 8.0078,
+      "mean_token_accuracy": 0.4434434473514557,
+      "num_tokens": 3873882.0,
+      "step": 228
+    },
+    {
+      "epoch": 0.0458,
+      "grad_norm": 11.591468811035156,
+      "learning_rate": 4.772e-06,
+      "loss": 8.237,
+      "mean_token_accuracy": 0.36707451939582825,
+      "num_tokens": 3888302.0,
+      "step": 229
+    },
+    {
+      "epoch": 0.046,
+      "grad_norm": 10.10312271118164,
+      "learning_rate": 4.7710000000000006e-06,
+      "loss": 7.6694,
+      "mean_token_accuracy": 0.5105820149183273,
+      "num_tokens": 3902804.0,
+      "step": 230
+    },
+    {
+      "epoch": 0.0462,
+      "grad_norm": 13.620348930358887,
+      "learning_rate": 4.77e-06,
+      "loss": 8.4942,
+      "mean_token_accuracy": 0.421875,
+      "num_tokens": 3922146.0,
+      "step": 231
+    },
+    {
+      "epoch": 0.0464,
+      "grad_norm": 11.014819145202637,
+      "learning_rate": 4.769e-06,
+      "loss": 7.637,
+      "mean_token_accuracy": 0.4495798349380493,
+      "num_tokens": 3936372.0,
+      "step": 232
+    },
+    {
+      "epoch": 0.0466,
+      "grad_norm": 14.10721492767334,
+      "learning_rate": 4.768000000000001e-06,
+      "loss": 7.4068,
+      "mean_token_accuracy": 0.5078571289777756,
+      "num_tokens": 3946456.0,
+      "step": 233
+    },
+    {
+      "epoch": 0.0468,
+      "grad_norm": 13.256854057312012,
+      "learning_rate": 4.767e-06,
+      "loss": 7.9252,
+      "mean_token_accuracy": 0.41277891397476196,
+      "num_tokens": 3965955.0,
+      "step": 234
+    },
+    {
+      "epoch": 0.047,
+      "grad_norm": 12.264280319213867,
+      "learning_rate": 4.766000000000001e-06,
+      "loss": 7.6561,
+      "mean_token_accuracy": 0.4913793057203293,
+      "num_tokens": 3980412.0,
+      "step": 235
+    },
+    {
+      "epoch": 0.0472,
+      "grad_norm": 11.942499160766602,
+      "learning_rate": 4.765e-06,
+      "loss": 8.0462,
+      "mean_token_accuracy": 0.4900284856557846,
+      "num_tokens": 3999823.0,
+      "step": 236
+    },
+    {
+      "epoch": 0.0474,
+      "grad_norm": 10.043482780456543,
+      "learning_rate": 4.7640000000000005e-06,
+      "loss": 7.0965,
+      "mean_token_accuracy": 0.4025973975658417,
+      "num_tokens": 4014414.0,
+      "step": 237
+    },
+    {
+      "epoch": 0.0476,
+      "grad_norm": 12.545036315917969,
+      "learning_rate": 4.763000000000001e-06,
+      "loss": 7.667,
+      "mean_token_accuracy": 0.38708220422267914,
+      "num_tokens": 4028922.0,
+      "step": 238
+    },
+    {
+      "epoch": 0.0478,
+      "grad_norm": 10.067218780517578,
+      "learning_rate": 4.762e-06,
+      "loss": 7.1117,
+      "mean_token_accuracy": 0.37129031121730804,
+      "num_tokens": 4050175.0,
+      "step": 239
+    },
+    {
+      "epoch": 0.048,
+      "grad_norm": 13.74410343170166,
+      "learning_rate": 4.761000000000001e-06,
+      "loss": 7.9069,
+      "mean_token_accuracy": 0.47333332896232605,
+      "num_tokens": 4064811.0,
+      "step": 240
+    },
+    {
+      "epoch": 0.0482,
+      "grad_norm": 9.813583374023438,
+      "learning_rate": 4.76e-06,
+      "loss": 6.8128,
+      "mean_token_accuracy": 0.4273170679807663,
+      "num_tokens": 4079317.0,
+      "step": 241
+    },
+    {
+      "epoch": 0.0484,
+      "grad_norm": 10.31633472442627,
+      "learning_rate": 4.7590000000000005e-06,
+      "loss": 7.676,
+      "mean_token_accuracy": 0.43584655225276947,
+      "num_tokens": 4094093.0,
+      "step": 242
+    },
+    {
+      "epoch": 0.0486,
+      "grad_norm": 13.174894332885742,
+      "learning_rate": 4.758e-06,
+      "loss": 8.5029,
+      "mean_token_accuracy": 0.42592592537403107,
+      "num_tokens": 4113778.0,
+      "step": 243
+    },
+    {
+      "epoch": 0.0488,
+      "grad_norm": 11.068340301513672,
+      "learning_rate": 4.757e-06,
+      "loss": 7.6392,
+      "mean_token_accuracy": 0.5028571337461472,
+      "num_tokens": 4125078.0,
+      "step": 244
+    },
+    {
+      "epoch": 0.049,
+      "grad_norm": 11.669493675231934,
+      "learning_rate": 4.756000000000001e-06,
+      "loss": 8.0877,
+      "mean_token_accuracy": 0.3697916716337204,
+      "num_tokens": 4144451.0,
+      "step": 245
+    },
+    {
+      "epoch": 0.0492,
+      "grad_norm": 12.121454238891602,
+      "learning_rate": 4.755e-06,
+      "loss": 8.3639,
+      "mean_token_accuracy": 0.3320707082748413,
+      "num_tokens": 4164189.0,
+      "step": 246
+    },
+    {
+      "epoch": 0.0494,
+      "grad_norm": 11.231935501098633,
+      "learning_rate": 4.7540000000000006e-06,
+      "loss": 8.1039,
+      "mean_token_accuracy": 0.40060852468013763,
+      "num_tokens": 4183560.0,
+      "step": 247
+    },
+    {
+      "epoch": 0.0496,
+      "grad_norm": 14.818300247192383,
+      "learning_rate": 4.753e-06,
+      "loss": 8.3393,
+      "mean_token_accuracy": 0.4365079402923584,
+      "num_tokens": 4203160.0,
+      "step": 248
+    },
+    {
+      "epoch": 0.0498,
+      "grad_norm": 10.595967292785645,
+      "learning_rate": 4.752e-06,
+      "loss": 8.2095,
+      "mean_token_accuracy": 0.3896551728248596,
+      "num_tokens": 4222502.0,
+      "step": 249
+    },
+    {
+      "epoch": 0.05,
+      "grad_norm": 10.283987998962402,
+      "learning_rate": 4.751000000000001e-06,
+      "loss": 7.8432,
+      "mean_token_accuracy": 0.41187499463558197,
+      "num_tokens": 4236999.0,
+      "step": 250
+    }
+  ],
+  "logging_steps": 1,
+  "max_steps": 5000,
+  "num_input_tokens_seen": 0,
+  "num_train_epochs": 1,
+  "save_steps": 250,
+  "stateful_callbacks": {
+    "TrainerControl": {
+      "args": {
+        "should_epoch_stop": false,
+        "should_evaluate": false,
+        "should_log": false,
+        "should_save": true,
+        "should_training_stop": false
+      },
+      "attributes": {}
+    }
+  },
+  "total_flos": 1.970126341013975e+17,
+  "train_batch_size": 1,
+  "trial_name": null,
+  "trial_params": null
+}

baseline-qwen2vl_sft-sft_colqwen-k2-train-29-APRIL-0_3/checkpoint-250/training_args.bin

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:552386998b88dd47fc2a23967a5c6beff7f2b7783f5e34527219b0a8f1d48205
+size 5816

baseline-qwen2vl_sft-sft_colqwen-k2-train-29-APRIL-0_3/checkpoint-500/README.md

@@ -0,0 +1,202 @@
+---
+base_model: Qwen/Qwen2.5-VL-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 0.15.2

baseline-qwen2vl_sft-sft_colqwen-k2-train-29-APRIL-0_3/checkpoint-500/adapter_config.json

@@ -0,0 +1,34 @@
+{
+  "alpha_pattern": {},
+  "auto_mapping": null,
+  "base_model_name_or_path": "Qwen/Qwen2.5-VL-7B-Instruct",
+  "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": 16,
+  "lora_bias": false,
+  "lora_dropout": 0.05,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "r": 8,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "q_proj",
+    "v_proj"
+  ],
+  "task_type": "CAUSAL_LM",
+  "trainable_token_indices": null,
+  "use_dora": false,
+  "use_rslora": false
+}

baseline-qwen2vl_sft-sft_colqwen-k2-train-29-APRIL-0_3/checkpoint-500/adapter_model.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:b8c80c92a9c25702a4416af4b6783f141f47a94fed375f300d85315bcef9f3b7
+size 10107280

baseline-qwen2vl_sft-sft_colqwen-k2-train-29-APRIL-0_3/checkpoint-500/added_tokens.json

@@ -0,0 +1,24 @@
+{
+  "</tool_call>": 151658,
+  "<tool_call>": 151657,
+  "<|box_end|>": 151649,
+  "<|box_start|>": 151648,
+  "<|endoftext|>": 151643,
+  "<|file_sep|>": 151664,
+  "<|fim_middle|>": 151660,
+  "<|fim_pad|>": 151662,
+  "<|fim_prefix|>": 151659,
+  "<|fim_suffix|>": 151661,
+  "<|im_end|>": 151645,
+  "<|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,
+  "<|vision_start|>": 151652
+}

baseline-qwen2vl_sft-sft_colqwen-k2-train-29-APRIL-0_3/checkpoint-500/optimizer.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:634521430b75312e7ac75dcaced0b6cbdb4f09667712e9dc40adf6c4fbcc6954
+size 20279354

baseline-qwen2vl_sft-sft_colqwen-k2-train-29-APRIL-0_3/checkpoint-500/rng_state.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:47225804ff95392a66d24cffda07bfcd22b73026ace32c85a52e639cea18a3a8
+size 14244

baseline-qwen2vl_sft-sft_colqwen-k2-train-29-APRIL-0_3/checkpoint-500/scheduler.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:f4ee1d47813d00a4e1e72607b91aa663b800ea0e750aa7e232f6a5ddab77a344
+size 1064

baseline-qwen2vl_sft-sft_colqwen-k2-train-29-APRIL-0_3/checkpoint-500/special_tokens_map.json

@@ -0,0 +1,31 @@
+{
+  "additional_special_tokens": [
+    "<|im_start|>",
+    "<|im_end|>",
+    "<|object_ref_start|>",
+    "<|object_ref_end|>",
+    "<|box_start|>",
+    "<|box_end|>",
+    "<|quad_start|>",
+    "<|quad_end|>",
+    "<|vision_start|>",
+    "<|vision_end|>",
+    "<|vision_pad|>",
+    "<|image_pad|>",
+    "<|video_pad|>"
+  ],
+  "eos_token": {
+    "content": "<|im_end|>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "pad_token": {
+    "content": "<|endoftext|>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  }
+}

baseline-qwen2vl_sft-sft_colqwen-k2-train-29-APRIL-0_3/checkpoint-500/tokenizer.json

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:9c5ae00e602b8860cbd784ba82a8aa14e8feecec692e7076590d014d7b7fdafa
+size 11421896

baseline-qwen2vl_sft-sft_colqwen-k2-train-29-APRIL-0_3/checkpoint-500/tokenizer_config.json

@@ -0,0 +1,208 @@
+{
+  "add_bos_token": false,
+  "add_prefix_space": false,
+  "added_tokens_decoder": {
+    "151643": {
+      "content": "<|endoftext|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151644": {
+      "content": "<|im_start|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151645": {
+      "content": "<|im_end|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151646": {
+      "content": "<|object_ref_start|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151647": {
+      "content": "<|object_ref_end|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151648": {
+      "content": "<|box_start|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151649": {
+      "content": "<|box_end|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151650": {
+      "content": "<|quad_start|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151651": {
+      "content": "<|quad_end|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151652": {
+      "content": "<|vision_start|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151653": {
+      "content": "<|vision_end|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151654": {
+      "content": "<|vision_pad|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151655": {
+      "content": "<|image_pad|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151656": {
+      "content": "<|video_pad|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151657": {
+      "content": "<tool_call>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151658": {
+      "content": "</tool_call>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151659": {
+      "content": "<|fim_prefix|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151660": {
+      "content": "<|fim_middle|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151661": {
+      "content": "<|fim_suffix|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151662": {
+      "content": "<|fim_pad|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151663": {
+      "content": "<|repo_name|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    },
+    "151664": {
+      "content": "<|file_sep|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    }
+  },
+  "additional_special_tokens": [
+    "<|im_start|>",
+    "<|im_end|>",
+    "<|object_ref_start|>",
+    "<|object_ref_end|>",
+    "<|box_start|>",
+    "<|box_end|>",
+    "<|quad_start|>",
+    "<|quad_end|>",
+    "<|vision_start|>",
+    "<|vision_end|>",
+    "<|vision_pad|>",
+    "<|image_pad|>",
+    "<|video_pad|>"
+  ],
+  "bos_token": null,
+  "chat_template": "{% set image_count = namespace(value=0) %}{% set video_count = namespace(value=0) %}{% for message in messages %}{% if loop.first and message['role'] != 'system' %}<|im_start|>system\nYou are a helpful assistant.<|im_end|>\n{% endif %}<|im_start|>{{ message['role'] }}\n{% if message['content'] is string %}{{ message['content'] }}<|im_end|>\n{% else %}{% for content in message['content'] %}{% if content['type'] == 'image' or 'image' in content or 'image_url' in content %}{% set image_count.value = image_count.value + 1 %}{% if add_vision_id %}Picture {{ image_count.value }}: {% endif %}<|vision_start|><|image_pad|><|vision_end|>{% elif content['type'] == 'video' or 'video' in content %}{% set video_count.value = video_count.value + 1 %}{% if add_vision_id %}Video {{ video_count.value }}: {% endif %}<|vision_start|><|video_pad|><|vision_end|>{% elif 'text' in content %}{{ content['text'] }}{% endif %}{% endfor %}<|im_end|>\n{% endif %}{% endfor %}{% if add_generation_prompt %}<|im_start|>assistant\n{% endif %}",
+  "clean_up_tokenization_spaces": false,
+  "eos_token": "<|im_end|>",
+  "errors": "replace",
+  "extra_special_tokens": {},
+  "model_max_length": 131072,
+  "pad_token": "<|endoftext|>",
+  "split_special_tokens": false,
+  "tokenizer_class": "Qwen2Tokenizer",
+  "unk_token": null
+}

baseline-qwen2vl_sft-sft_colqwen-k2-train-29-APRIL-0_3/checkpoint-500/training_args.bin

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:552386998b88dd47fc2a23967a5c6beff7f2b7783f5e34527219b0a8f1d48205
+size 5816

baseline-qwen2vl_sft-sft_colqwen-k2-train-29-APRIL-0_3/checkpoint-750/README.md

@@ -0,0 +1,202 @@
+---
+base_model: Qwen/Qwen2.5-VL-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 0.15.2

baseline-qwen2vl_sft-sft_colqwen-k2-train-29-APRIL-0_3/checkpoint-750/adapter_config.json

@@ -0,0 +1,34 @@
+{
+  "alpha_pattern": {},
+  "auto_mapping": null,
+  "base_model_name_or_path": "Qwen/Qwen2.5-VL-7B-Instruct",
+  "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": 16,
+  "lora_bias": false,
+  "lora_dropout": 0.05,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "r": 8,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "q_proj",
+    "v_proj"
+  ],
+  "task_type": "CAUSAL_LM",
+  "trainable_token_indices": null,
+  "use_dora": false,
+  "use_rslora": false
+}

baseline-qwen2vl_sft-sft_colqwen-k2-train-29-APRIL-0_3/checkpoint-750/adapter_model.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:edc8e99d87e6e60907281cf4e3684e91a850cb6d46b44f75b45bebf9b4fd60c0
+size 10107280

baseline-qwen2vl_sft-sft_colqwen-k2-train-29-APRIL-0_3/checkpoint-750/added_tokens.json

@@ -0,0 +1,24 @@
+{
+  "</tool_call>": 151658,
+  "<tool_call>": 151657,
+  "<|box_end|>": 151649,
+  "<|box_start|>": 151648,
+  "<|endoftext|>": 151643,
+  "<|file_sep|>": 151664,
+  "<|fim_middle|>": 151660,
+  "<|fim_pad|>": 151662,
+  "<|fim_prefix|>": 151659,
+  "<|fim_suffix|>": 151661,
+  "<|im_end|>": 151645,
+  "<|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,
+  "<|vision_start|>": 151652
+}

baseline-qwen2vl_sft-sft_colqwen-k2-train-29-APRIL-0_3/checkpoint-750/optimizer.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:a6426574cc99c29ddc51a6b6112c38e4c3ffb5c67ffac6caffb5fc6199ef7f1d
+size 20279354

baseline-qwen2vl_sft-sft_colqwen-k2-train-29-APRIL-0_3/checkpoint-750/rng_state.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:a3e0761f5d735d3e0af3e96783bb63e61cf21b8444a1b15db1eee557804b0ea0
+size 14244