final_model_5
This model is a fine-tuned version of mistralai/Mistral-7B-Instruct-v0.2 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 2.8725
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
The following bitsandbytes
quantization config was used during training:
- quant_method: bitsandbytes
- load_in_8bit: False
- load_in_4bit: True
- llm_int8_threshold: 6.0
- llm_int8_skip_modules: None
- llm_int8_enable_fp32_cpu_offload: False
- llm_int8_has_fp16_weight: False
- bnb_4bit_quant_type: nf4
- bnb_4bit_use_double_quant: False
- bnb_4bit_compute_dtype: bfloat16
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0002
- train_batch_size: 8
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.03
- training_steps: 90
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
0.0462 | 1.0 | 1 | 2.5821 |
0.0463 | 2.0 | 2 | 2.6255 |
0.0327 | 3.0 | 3 | 2.7177 |
0.0374 | 4.0 | 4 | 2.7702 |
0.0465 | 5.0 | 5 | 2.7528 |
0.029 | 6.0 | 6 | 2.7269 |
0.0239 | 7.0 | 7 | 2.6977 |
0.0284 | 8.0 | 8 | 2.6762 |
0.019 | 9.0 | 9 | 2.6788 |
0.0184 | 10.0 | 10 | 2.6653 |
0.0283 | 11.0 | 11 | 2.6582 |
0.0232 | 12.0 | 12 | 2.6511 |
0.0161 | 13.0 | 13 | 2.6508 |
0.0158 | 14.0 | 14 | 2.6450 |
0.0147 | 15.0 | 15 | 2.6431 |
0.0156 | 16.0 | 16 | 2.6449 |
0.014 | 17.0 | 17 | 2.6488 |
0.0139 | 18.0 | 18 | 2.6530 |
0.0137 | 19.0 | 19 | 2.6587 |
0.0136 | 20.0 | 20 | 2.6646 |
0.0135 | 21.0 | 21 | 2.6703 |
0.0134 | 22.0 | 22 | 2.6755 |
0.0133 | 23.0 | 23 | 2.6806 |
0.0131 | 24.0 | 24 | 2.6858 |
0.0131 | 25.0 | 25 | 2.6908 |
0.0129 | 26.0 | 26 | 2.6956 |
0.0128 | 27.0 | 27 | 2.7001 |
0.0127 | 28.0 | 28 | 2.7043 |
0.0125 | 29.0 | 29 | 2.7083 |
0.0123 | 30.0 | 30 | 2.7120 |
0.0121 | 31.0 | 31 | 2.7155 |
0.0121 | 32.0 | 32 | 2.7191 |
0.0117 | 33.0 | 33 | 2.7227 |
0.0115 | 34.0 | 34 | 2.7263 |
0.0113 | 35.0 | 35 | 2.7301 |
0.0111 | 36.0 | 36 | 2.7340 |
0.0108 | 37.0 | 37 | 2.7379 |
0.0106 | 38.0 | 38 | 2.7418 |
0.0104 | 39.0 | 39 | 2.7457 |
0.0104 | 40.0 | 40 | 2.7494 |
0.01 | 41.0 | 41 | 2.7532 |
0.0098 | 42.0 | 42 | 2.7569 |
0.0096 | 43.0 | 43 | 2.7606 |
0.0095 | 44.0 | 44 | 2.7643 |
0.0094 | 45.0 | 45 | 2.7681 |
0.0093 | 46.0 | 46 | 2.7720 |
0.0093 | 47.0 | 47 | 2.7760 |
0.0092 | 48.0 | 48 | 2.7802 |
0.0092 | 49.0 | 49 | 2.7846 |
0.0091 | 50.0 | 50 | 2.7892 |
0.0091 | 51.0 | 51 | 2.7940 |
0.0091 | 52.0 | 52 | 2.7989 |
0.0091 | 53.0 | 53 | 2.8039 |
0.009 | 54.0 | 54 | 2.8090 |
0.009 | 55.0 | 55 | 2.8141 |
0.0089 | 56.0 | 56 | 2.8191 |
0.0089 | 57.0 | 57 | 2.8239 |
0.0088 | 58.0 | 58 | 2.8284 |
0.0087 | 59.0 | 59 | 2.8331 |
0.0088 | 60.0 | 60 | 2.8372 |
0.0087 | 61.0 | 61 | 2.8405 |
0.0087 | 62.0 | 62 | 2.8433 |
0.0086 | 63.0 | 63 | 2.8457 |
0.0086 | 64.0 | 64 | 2.8476 |
0.0085 | 65.0 | 65 | 2.8499 |
0.0085 | 66.0 | 66 | 2.8514 |
0.0085 | 67.0 | 67 | 2.8530 |
0.0084 | 68.0 | 68 | 2.8545 |
0.0084 | 69.0 | 69 | 2.8560 |
0.0084 | 70.0 | 70 | 2.8575 |
0.0084 | 71.0 | 71 | 2.8590 |
0.0083 | 72.0 | 72 | 2.8605 |
0.0083 | 73.0 | 73 | 2.8620 |
0.0083 | 74.0 | 74 | 2.8633 |
0.0082 | 75.0 | 75 | 2.8646 |
0.0082 | 76.0 | 76 | 2.8657 |
0.0082 | 77.0 | 77 | 2.8668 |
0.0082 | 78.0 | 78 | 2.8679 |
0.0081 | 79.0 | 79 | 2.8689 |
0.0082 | 80.0 | 80 | 2.8697 |
0.0082 | 81.0 | 81 | 2.8705 |
0.0081 | 82.0 | 82 | 2.8711 |
0.0082 | 83.0 | 83 | 2.8716 |
0.0082 | 84.0 | 84 | 2.8719 |
0.0081 | 85.0 | 85 | 2.8721 |
0.0081 | 86.0 | 86 | 2.8723 |
0.0081 | 87.0 | 87 | 2.8724 |
0.0081 | 88.0 | 88 | 2.8724 |
0.0081 | 89.0 | 89 | 2.8725 |
0.0081 | 90.0 | 90 | 2.8725 |
Framework versions
- PEFT 0.4.0
- Transformers 4.37.2
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.15.2
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Model tree for hussamsal/final_model_5
Base model
mistralai/Mistral-7B-Instruct-v0.2