Model save
Browse files- README.md +59 -0
- adapter_model.safetensors +1 -1
- all_results.json +13 -0
- config_argument.yaml +52 -0
- eval_results.json +8 -0
- train_results.json +8 -0
- trainer_state.json +1182 -0
README.md
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+
---
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base_model: hllj/mistral-vi-math
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tags:
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- generated_from_trainer
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model-index:
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- name: sft-mistral-v1-clean-valid
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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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# sft-mistral-v1-clean-valid
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This model is a fine-tuned version of [hllj/mistral-vi-math](https://huggingface.co/hllj/mistral-vi-math) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.5125
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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: 3e-05
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- train_batch_size: 4
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- eval_batch_size: 4
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- seed: 42
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- distributed_type: multi-GPU
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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: 0.05
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- num_epochs: 2
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- mixed_precision_training: Native AMP
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### Training results
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| Training Loss | Epoch | Step | Validation Loss |
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|:-------------:|:-----:|:----:|:---------------:|
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| 0.312 | 1.02 | 1000 | 0.5086 |
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### Framework versions
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- Transformers 4.35.2
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- Pytorch 2.1.0
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- Datasets 2.15.0
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- Tokenizers 0.15.0
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adapter_model.safetensors
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version https://git-lfs.github.com/spec/v1
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-
oid sha256:
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size 872450448
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version https://git-lfs.github.com/spec/v1
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+
oid sha256:519bc1b9c59aefeafd8b9c396f2b89396d75513f3f348154282adb4901cb71c2
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size 872450448
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all_results.json
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{
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"epoch": 1.45,
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"eval_loss": 0.5124574303627014,
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"eval_runtime": 6.883,
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"eval_samples": 140,
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"eval_samples_per_second": 20.34,
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"eval_steps_per_second": 5.085,
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"train_loss": 0.32689529290324765,
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| 9 |
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"train_runtime": 3915.3355,
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+
"train_samples": 8517,
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"train_samples_per_second": 4.351,
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"train_steps_per_second": 1.088
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}
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config_argument.yaml
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cache_dir: ./cache
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ddp_find_unused_parameters: false
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ddp_timeout: 30000
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device_map: auto
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do_eval: true
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do_train: true
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eval_steps: 1000
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evaluation_strategy: steps
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fp16: true
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gradient_accumulation_steps: 1
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gradient_checkpointing: true
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gradient_checkpointing_kwargs:
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use_reentrant: false
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hub_model_id: hllj/sft-mistral-v1-clean-valid
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hub_strategy: every_save
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learning_rate: 3.0e-05
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log_level: info
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logging_first_step: true
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logging_steps: 10
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logging_strategy: steps
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lora_alpha: 128
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lora_dropout: 0.05
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lora_r: 256
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lora_target_modules:
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- q_proj
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- k_proj
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- v_proj
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- o_proj
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lr_scheduler_type: cosine
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max_seq_length: 1024
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model_name_or_path: hllj/mistral-vi-math
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model_type: auto
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num_train_epochs: 2
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output_dir: outputs-sft-mistral-v1-clean-valid
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overwrite_output_dir: true
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per_device_eval_batch_size: 4
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per_device_train_batch_size: 4
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preprocessing_num_workers: 4
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push_to_hub: true
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report_to: wandb
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run_name: sft-mistral-v1-clean-valid
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save_steps: 1000
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save_strategy: steps
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save_total_limit: 13
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seed: 42
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token: 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
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torch_dtype: float16
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train_file_dir: datasets/finetune
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use_peft: true
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validation_file_dir: datasets/validation
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warmup_ratio: 0.05
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weight_decay: 0.05
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eval_results.json
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{
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"epoch": 1.45,
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"eval_loss": 0.5124574303627014,
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"eval_runtime": 6.883,
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| 5 |
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"eval_samples": 140,
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"eval_samples_per_second": 20.34,
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"eval_steps_per_second": 5.085
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}
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train_results.json
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{
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"epoch": 1.45,
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"train_loss": 0.32689529290324765,
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+
"train_runtime": 3915.3355,
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| 5 |
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"train_samples": 8517,
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"train_samples_per_second": 4.351,
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| 7 |
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"train_steps_per_second": 1.088
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}
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trainer_state.json
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