bbabfc674b
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| .. | ||
| checkpoint-45 | ||
| README.md | ||
| adapter_config.json | ||
| adapter_model.safetensors | ||
| added_tokens.json | ||
| all_results.json | ||
| eval_results.json | ||
| special_tokens_map.json | ||
| tokenizer.json | ||
| tokenizer.model | ||
| tokenizer_config.json | ||
| train_results.json | ||
| trainer_log.jsonl | ||
| trainer_state.json | ||
| training_args.bin | ||
README.md
| base_model | library_name | license | tags | model-index | ||||||||
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| /home/user/.cache/modelscope/hub/modelscope/Llama-2-7b-ms | peft | other |
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sft
This model is a fine-tuned version of /home/user/.cache/modelscope/hub/modelscope/Llama-2-7b-ms on the identity and the alpaca_en_demo datasets. It achieves the following results on the evaluation set:
- Loss: nan
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0001
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 8
- total_train_batch_size: 64
- total_eval_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 20
- num_epochs: 3.0
- mixed_precision_training: Native AMP
Training results
Framework versions
- PEFT 0.12.0
- Transformers 4.43.4
- Pytorch 2.4.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1