Model save
Browse files- README.md +40 -38
- last_checkpoint/config.json +7 -1
- last_checkpoint/model-00001-of-00003.safetensors +3 -0
- last_checkpoint/model-00002-of-00003.safetensors +3 -0
- last_checkpoint/model-00003-of-00003.safetensors +3 -0
- last_checkpoint/model.safetensors.index.json +328 -328
- last_checkpoint/tokenizer.json +2 -2
- last_checkpoint/training_args.bin +2 -2
README.md
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---
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base_model: mistralai/Ministral-8B-Instruct-2410
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library_name: transformers
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tags:
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- generated_from_trainer
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---
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It has been trained using [TRL](https://github.com/huggingface/trl).
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from transformers import pipeline
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generator = pipeline("text-generation", model="RyanYr/reflect_Mini8B_nonGenCritic_Mini8bT0GtT1MstllrgT2_SftT2", 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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##
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- Transformers: 4.45.2
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- Pytorch: 2.5.1
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- Datasets: 3.1.0
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- Tokenizers: 0.20.3
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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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---
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library_name: transformers
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license: other
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base_model: mistralai/Ministral-8B-Instruct-2410
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tags:
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- generated_from_trainer
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model-index:
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- name: reflectNonGenCrtc_om2_Mini8bT0MstrllrgT12-460k_OrmCritic
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# reflectNonGenCrtc_om2_Mini8bT0MstrllrgT12-460k_OrmCritic
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This model is a fine-tuned version of [mistralai/Ministral-8B-Instruct-2410](https://huggingface.co/mistralai/Ministral-8B-Instruct-2410) on an unknown dataset.
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 1e-06
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- train_batch_size: 1
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- eval_batch_size: 1
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- seed: 42
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- distributed_type: multi-GPU
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- num_devices: 4
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- gradient_accumulation_steps: 64
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- total_train_batch_size: 256
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- total_eval_batch_size: 4
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: cosine
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- lr_scheduler_warmup_ratio: 0.03
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- num_epochs: 1
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### Training results
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### Framework versions
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- Transformers 4.45.2
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- Pytorch 2.5.1+cu124
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- Datasets 3.1.0
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- Tokenizers 0.20.3
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last_checkpoint/config.json
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{
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"_name_or_path": "mistralai/Ministral-8B-Instruct-2410",
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"architectures": [
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"
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"attention_dropout": 0.0,
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"bos_token_id": 1,
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"head_dim": 128,
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"hidden_act": "silu",
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"hidden_size": 4096,
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"initializer_range": 0.02,
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{
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"attention_dropout": 0.0,
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"head_dim": 128,
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"hidden_act": "silu",
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"hidden_size": 4096,
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"id2label": {
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"0": "LABEL_0"
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"label2id": {
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},
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"max_position_embeddings": 32768,
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"model_type": "mistral",
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"num_attention_heads": 32,
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last_checkpoint/model-00001-of-00003.safetensors
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last_checkpoint/model.safetensors.index.json
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last_checkpoint/tokenizer.json
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last_checkpoint/training_args.bin
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