Model save
Browse files- README.md +58 -0
- all_results.json +9 -0
- chat_template.json +3 -0
- generation_config.json +15 -0
- preprocessor_config.json +29 -0
- train_results.json +9 -0
- trainer_state.json +940 -0
README.md
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---
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base_model: Qwen/Qwen2-VL-2B-Instruct
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library_name: transformers
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model_name: Qwen2-VL-2B-Instruct-SFT
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tags:
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- generated_from_trainer
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- trl
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- sft
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licence: license
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---
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# Model Card for Qwen2-VL-2B-Instruct-SFT
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This model is a fine-tuned version of [Qwen/Qwen2-VL-2B-Instruct](https://huggingface.co/Qwen/Qwen2-VL-2B-Instruct).
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It has been trained using [TRL](https://github.com/huggingface/trl).
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## Quick start
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```python
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from transformers import pipeline
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question = "If you had a time machine, but could only go to the past or the future once and never return, which would you choose and why?"
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generator = pipeline("text-generation", model="bluuluu/Qwen2-VL-2B-Instruct-SFT", device="cuda")
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output = generator([{"role": "user", "content": question}], max_new_tokens=128, return_full_text=False)[0]
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print(output["generated_text"])
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```
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## Training procedure
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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="150" height="24"/>](https://wandb.ai/2741919970-hustvl/huggingface/runs/hxbtcd5t)
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This model was trained with SFT.
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### Framework versions
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- TRL: 0.14.0
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- Transformers: 4.51.1
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- Pytorch: 2.5.1
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- Datasets: 3.2.0
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- Tokenizers: 0.21.1
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## Citations
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Cite TRL as:
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```bibtex
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@misc{vonwerra2022trl,
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title = {{TRL: Transformer Reinforcement Learning}},
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author = {Leandro von Werra and Younes Belkada and Lewis Tunstall and Edward Beeching and Tristan Thrush and Nathan Lambert and Shengyi Huang and Kashif Rasul and Quentin Gallouédec},
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year = 2020,
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journal = {GitHub repository},
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publisher = {GitHub},
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howpublished = {\url{https://github.com/huggingface/trl}}
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}
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```
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all_results.json
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{
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"epoch": 0.9990182603573532,
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"total_flos": 3801667199303680.0,
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"train_loss": 0.13866351419509207,
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"train_runtime": 19174.2073,
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"train_samples": 40742,
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"train_samples_per_second": 2.125,
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"train_steps_per_second": 0.033
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}
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chat_template.json
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{
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"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 %}"
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}
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generation_config.json
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{
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"attn_implementation": null,
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"bos_token_id": 151643,
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"do_sample": true,
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"eos_token_id": [
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151645,
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151643
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],
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"pad_token_id": 151643,
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"temperature": 0.01,
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"top_k": 1,
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"top_p": 0.001,
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"transformers_version": "4.51.1",
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"use_cache": false
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}
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preprocessor_config.json
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{
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"do_convert_rgb": true,
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"do_normalize": true,
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"do_rescale": true,
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"do_resize": true,
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"image_mean": [
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0.48145466,
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0.4578275,
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0.40821073
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],
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"image_processor_type": "Qwen2VLImageProcessor",
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"image_std": [
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0.26862954,
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0.26130258,
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0.27577711
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],
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"max_pixels": 12845056,
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"merge_size": 2,
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"min_pixels": 3136,
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"patch_size": 14,
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"processor_class": "Qwen2VLProcessor",
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"resample": 3,
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"rescale_factor": 0.00392156862745098,
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"size": {
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"longest_edge": 12845056,
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"shortest_edge": 3136
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},
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"temporal_patch_size": 2
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}
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train_results.json
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{
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"epoch": 0.9990182603573532,
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"total_flos": 3801667199303680.0,
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"train_loss": 0.13866351419509207,
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"train_runtime": 19174.2073,
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"train_samples": 40742,
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"train_samples_per_second": 2.125,
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"train_steps_per_second": 0.033
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}
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trainer_state.json
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