End of training
Browse files- README.md +15 -15
- adapter_config.json +2 -2
- adapter_model.safetensors +1 -1
- metrics.jsonl +6 -0
- metrics_epoch_0.96_fold_0_lr_0.0001_seed_1234_weight_10.0.json +1 -0
- metrics_epoch_2.0_fold_0_lr_0.0001_seed_1234_weight_10.0.json +1 -0
- metrics_epoch_2.96_fold_0_lr_0.0001_seed_1234_weight_10.0.json +1 -0
- metrics_epoch_4.0_fold_0_lr_0.0001_seed_1234_weight_10.0.json +1 -0
- metrics_epoch_4.96_fold_0_lr_0.0001_seed_1234_weight_10.0.json +1 -0
- metrics_epoch_5.76_fold_0_lr_0.0001_seed_1234_weight_10.0.json +1 -0
- results_epoch_0.96_fold_0_lr_0.0001_seed_1234_weight_10.0.json +0 -0
- results_epoch_2.0_fold_0_lr_0.0001_seed_1234_weight_10.0.json +0 -0
- results_epoch_2.96_fold_0_lr_0.0001_seed_1234_weight_10.0.json +0 -0
- results_epoch_4.0_fold_0_lr_0.0001_seed_1234_weight_10.0.json +0 -0
- results_epoch_4.96_fold_0_lr_0.0001_seed_1234_weight_10.0.json +0 -0
- results_epoch_5.76_fold_0_lr_0.0001_seed_1234_weight_10.0.json +0 -0
- training_args.bin +1 -1
README.md
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This model is a fine-tuned version of [meta-llama/Meta-Llama-3-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.
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- Eval/rewards/chosen: -
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- Eval/logps/chosen: -
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- Eval/rewards/rejected: -
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- Eval/logps/rejected: -
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- Eval/rewards/margins:
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- Eval/kl: 0.0
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## Model description
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate:
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- train_batch_size: 1
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- eval_batch_size: 2
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- seed: 1234
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### Training results
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| Training Loss | Epoch | Step | Validation Loss |
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### Framework versions
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This model is a fine-tuned version of [meta-llama/Meta-Llama-3-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.8136
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- Eval/rewards/chosen: -15.7423
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- Eval/logps/chosen: -350.2482
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- Eval/rewards/rejected: -21.6619
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- Eval/logps/rejected: -446.4881
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- Eval/rewards/margins: 5.9196
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- Eval/kl: 0.0
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## Model description
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 0.0001
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- train_batch_size: 1
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- eval_batch_size: 2
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- seed: 1234
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | |
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| 0.4474 | 0.96 | 12 | 0.8052 | 0.0 |
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| 0.625 | 2.0 | 25 | 0.8136 | 0.0 |
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| 0.375 | 2.96 | 37 | 0.8136 | 0.0 |
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| 0.625 | 4.0 | 50 | 0.8136 | 0.0 |
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| 0.375 | 4.96 | 62 | 0.8136 | 0.0 |
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| 0.625 | 5.76 | 72 | 0.8136 | 0.0 |
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### Framework versions
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adapter_config.json
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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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"v_proj",
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"q_proj",
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"o_proj"
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],
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"task_type": "CAUSAL_LM",
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"rank_pattern": {},
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"revision": null,
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"target_modules": [
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"q_proj",
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"v_proj",
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"k_proj",
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"o_proj"
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],
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"task_type": "CAUSAL_LM",
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adapter_model.safetensors
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metrics.jsonl
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{"epoch": 4.0, "precision": 0.5454545438016529, "recall": 0.9999999944444444, "fold": 0}
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{"epoch": 4.96, "precision": 0.49999999852941174, "recall": 0.9444444391975308, "fold": 0}
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{"epoch": 5.76, "precision": 0.47058823391003457, "recall": 0.8888888839506173, "fold": 0}
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{"epoch": 4.0, "precision": 0.5454545438016529, "recall": 0.9999999944444444, "fold": 0}
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{"epoch": 4.96, "precision": 0.49999999852941174, "recall": 0.9444444391975308, "fold": 0}
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{"epoch": 5.76, "precision": 0.47058823391003457, "recall": 0.8888888839506173, "fold": 0}
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{"epoch": 0.96, "precision": 0.7999999946666667, "recall": 0.666666662962963, "fold": 0}
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{"epoch": 2.0, "precision": 0.9999999500000026, "recall": 0.11111111049382716, "fold": 0}
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{"epoch": 2.96, "precision": 0.0, "recall": 0.0, "fold": 0}
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{"epoch": 4.0, "precision": 0.0, "recall": 0.0, "fold": 0}
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{"epoch": 4.96, "precision": 0.0, "recall": 0.0, "fold": 0}
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{"epoch": 5.76, "precision": 0.0, "recall": 0.0, "fold": 0}
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metrics_epoch_0.96_fold_0_lr_0.0001_seed_1234_weight_10.0.json
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{"epoch": 0.96, "precision": 0.7999999946666667, "recall": 0.666666662962963, "fold": 0}
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metrics_epoch_2.0_fold_0_lr_0.0001_seed_1234_weight_10.0.json
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{"epoch": 2.0, "precision": 0.9999999500000026, "recall": 0.11111111049382716, "fold": 0}
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metrics_epoch_2.96_fold_0_lr_0.0001_seed_1234_weight_10.0.json
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{"epoch": 2.96, "precision": 0.0, "recall": 0.0, "fold": 0}
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metrics_epoch_4.0_fold_0_lr_0.0001_seed_1234_weight_10.0.json
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{"epoch": 4.0, "precision": 0.0, "recall": 0.0, "fold": 0}
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{"epoch": 4.96, "precision": 0.0, "recall": 0.0, "fold": 0}
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metrics_epoch_5.76_fold_0_lr_0.0001_seed_1234_weight_10.0.json
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{"epoch": 5.76, "precision": 0.0, "recall": 0.0, "fold": 0}
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results_epoch_0.96_fold_0_lr_0.0001_seed_1234_weight_10.0.json
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results_epoch_2.0_fold_0_lr_0.0001_seed_1234_weight_10.0.json
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results_epoch_2.96_fold_0_lr_0.0001_seed_1234_weight_10.0.json
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results_epoch_4.0_fold_0_lr_0.0001_seed_1234_weight_10.0.json
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results_epoch_4.96_fold_0_lr_0.0001_seed_1234_weight_10.0.json
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results_epoch_5.76_fold_0_lr_0.0001_seed_1234_weight_10.0.json
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training_args.bin
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