ahmedgongi10
commited on
ahmedgongi10/mistral_version1
Browse files- README.md +15 -19
- adapter_config.json +6 -6
- adapter_model.safetensors +2 -2
- training_args.bin +1 -1
README.md
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@@ -16,7 +16,7 @@ should probably proofread and complete it, then remove this comment. -->
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This model is a fine-tuned version of [mistralai/Mistral-7B-Instruct-v0.2](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss:
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## Model description
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The following hyperparameters were used during training:
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- learning_rate: 0.0002
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- train_batch_size:
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- eval_batch_size:
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- seed: 42
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- gradient_accumulation_steps:
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- total_train_batch_size:
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type:
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- lr_scheduler_warmup_steps: 2
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- num_epochs:
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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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| 1.
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| 0.4464 | 6.0 | 612 | 1.5966 |
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| 0.3066 | 7.0 | 714 | 1.7195 |
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| 0.2135 | 8.0 | 816 | 1.8925 |
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| 0.1534 | 9.0 | 918 | 2.0300 |
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| 0.1169 | 10.0 | 1020 | 2.1539 |
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### Framework versions
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- PEFT 0.
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- Transformers 4.
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- Pytorch 2.1.2
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- Datasets 2.1.0
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- Tokenizers 0.15.2
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This model is a fine-tuned version of [mistralai/Mistral-7B-Instruct-v0.2](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.0892
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## Model description
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The following hyperparameters were used during training:
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- learning_rate: 0.0002
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- train_batch_size: 4
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- eval_batch_size: 2
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- seed: 42
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- gradient_accumulation_steps: 2
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- total_train_batch_size: 8
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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: 0.1
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- lr_scheduler_warmup_steps: 2
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- num_epochs: 1
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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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| 1.0643 | 0.17 | 100 | 1.1166 |
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| 1.0302 | 0.34 | 200 | 1.1029 |
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| 1.1972 | 0.51 | 300 | 1.0958 |
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| 1.1332 | 0.68 | 400 | 1.0910 |
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| 1.0084 | 0.85 | 500 | 1.0892 |
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### Framework versions
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- PEFT 0.10.0
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- Transformers 4.39.0
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- Pytorch 2.1.2
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- Datasets 2.1.0
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- Tokenizers 0.15.2
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adapter_config.json
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{
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"alpha_pattern": {},
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"auto_mapping": null,
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"base_model_name_or_path":
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"bias": "none",
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"fan_in_fan_out": false,
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"inference_mode": true,
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"layers_pattern": null,
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"layers_to_transform": null,
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"loftq_config": {},
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"lora_alpha":
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"lora_dropout": 0.1,
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"megatron_config": null,
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"megatron_core": "megatron.core",
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"modules_to_save": null,
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"peft_type": "LORA",
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"r":
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"rank_pattern": {},
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"revision": null,
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"target_modules": [
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"v_proj",
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"k_proj",
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"
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"
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],
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"task_type": "CAUSAL_LM",
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"use_dora": false,
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{
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"alpha_pattern": {},
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"auto_mapping": null,
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"base_model_name_or_path": "mistralai/Mistral-7B-Instruct-v0.2",
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"bias": "none",
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"fan_in_fan_out": false,
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"inference_mode": true,
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"layers_pattern": null,
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"layers_to_transform": null,
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"loftq_config": {},
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"lora_alpha": 16,
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"lora_dropout": 0.1,
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"megatron_config": null,
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"megatron_core": "megatron.core",
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"modules_to_save": null,
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"peft_type": "LORA",
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"r": 8,
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"rank_pattern": {},
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"revision": null,
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"target_modules": [
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"k_proj",
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"o_proj",
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"v_proj",
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"q_proj"
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],
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"task_type": "CAUSAL_LM",
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"use_dora": false,
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adapter_model.safetensors
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size
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training_args.bin
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version https://git-lfs.github.com/spec/v1
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