v3c_mistral_lora
This model is a fine-tuned version of peiyi9979/math-shepherd-mistral-7b-prm on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.2939
- Accuracy: 0.8636
- Precision: 0.8421
- Recall: 0.6324
- F1: 0.7223
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: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 765837
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- total_eval_batch_size: 32
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 1
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
---|---|---|---|---|---|---|---|
No log | 0 | 0 | 0.6026 | 0.7339 | 0.6 | 0.1542 | 0.2453 |
0.6391 | 0.0248 | 20 | 0.5954 | 0.7361 | 0.6119 | 0.1621 | 0.2562 |
0.5891 | 0.0495 | 40 | 0.5570 | 0.7550 | 0.6176 | 0.3320 | 0.4319 |
0.4606 | 0.0743 | 60 | 0.4962 | 0.7794 | 0.6667 | 0.4269 | 0.5205 |
0.4229 | 0.0990 | 80 | 0.4433 | 0.7905 | 0.6649 | 0.5099 | 0.5772 |
0.3836 | 0.1238 | 100 | 0.4297 | 0.8160 | 0.7605 | 0.5020 | 0.6048 |
0.3363 | 0.1485 | 120 | 0.3676 | 0.8381 | 0.7892 | 0.5771 | 0.6667 |
0.2483 | 0.1733 | 140 | 0.3537 | 0.8404 | 0.8225 | 0.5494 | 0.6588 |
0.2803 | 0.1980 | 160 | 0.3468 | 0.8415 | 0.8481 | 0.5296 | 0.6521 |
0.2782 | 0.2228 | 180 | 0.3493 | 0.8237 | 0.8310 | 0.4664 | 0.5975 |
0.2174 | 0.2475 | 200 | 0.3329 | 0.8492 | 0.8232 | 0.5889 | 0.6866 |
0.2965 | 0.2723 | 220 | 0.3314 | 0.8448 | 0.8343 | 0.5573 | 0.6682 |
0.2379 | 0.2970 | 240 | 0.3736 | 0.8149 | 0.8468 | 0.4150 | 0.5570 |
0.1587 | 0.3218 | 260 | 0.3315 | 0.8404 | 0.8609 | 0.5138 | 0.6436 |
0.1769 | 0.3465 | 280 | 0.3329 | 0.8370 | 0.8313 | 0.5257 | 0.6441 |
0.1984 | 0.3713 | 300 | 0.3211 | 0.8537 | 0.8712 | 0.5613 | 0.6827 |
0.2109 | 0.3960 | 320 | 0.3064 | 0.8570 | 0.8333 | 0.6126 | 0.7062 |
0.1961 | 0.4208 | 340 | 0.3035 | 0.8625 | 0.8413 | 0.6285 | 0.7195 |
0.2369 | 0.4455 | 360 | 0.2959 | 0.8747 | 0.8365 | 0.6877 | 0.7549 |
0.2355 | 0.4703 | 380 | 0.3176 | 0.8537 | 0.8380 | 0.5929 | 0.6944 |
0.1538 | 0.4950 | 400 | 0.3098 | 0.8503 | 0.8554 | 0.5613 | 0.6778 |
0.2261 | 0.5198 | 420 | 0.2964 | 0.8659 | 0.8235 | 0.6640 | 0.7352 |
0.1894 | 0.5446 | 440 | 0.3085 | 0.8625 | 0.8772 | 0.5929 | 0.7075 |
0.2089 | 0.5693 | 460 | 0.3103 | 0.8592 | 0.8621 | 0.5929 | 0.7026 |
0.225 | 0.5941 | 480 | 0.2933 | 0.8670 | 0.8519 | 0.6364 | 0.7285 |
0.2837 | 0.6188 | 500 | 0.2955 | 0.8636 | 0.8283 | 0.6482 | 0.7273 |
0.2046 | 0.6436 | 520 | 0.2943 | 0.8647 | 0.8429 | 0.6364 | 0.7252 |
0.1548 | 0.6683 | 540 | 0.3003 | 0.8636 | 0.8421 | 0.6324 | 0.7223 |
0.1626 | 0.6931 | 560 | 0.2982 | 0.8625 | 0.8603 | 0.6087 | 0.7130 |
0.2065 | 0.7178 | 580 | 0.2877 | 0.8636 | 0.8186 | 0.6601 | 0.7309 |
0.1423 | 0.7426 | 600 | 0.3031 | 0.8603 | 0.8757 | 0.5850 | 0.7014 |
0.1743 | 0.7673 | 620 | 0.2920 | 0.8659 | 0.8511 | 0.6324 | 0.7256 |
0.1281 | 0.7921 | 640 | 0.2912 | 0.8659 | 0.8474 | 0.6364 | 0.7269 |
0.1879 | 0.8168 | 660 | 0.2938 | 0.8625 | 0.8449 | 0.6245 | 0.7182 |
0.1741 | 0.8416 | 680 | 0.2965 | 0.8625 | 0.8486 | 0.6206 | 0.7169 |
0.1429 | 0.8663 | 700 | 0.2911 | 0.8647 | 0.8359 | 0.6443 | 0.7277 |
0.2218 | 0.8911 | 720 | 0.2950 | 0.8625 | 0.8449 | 0.6245 | 0.7182 |
0.1608 | 0.9158 | 740 | 0.2995 | 0.8603 | 0.8508 | 0.6087 | 0.7097 |
0.2056 | 0.9406 | 760 | 0.2967 | 0.8592 | 0.8424 | 0.6126 | 0.7094 |
0.2127 | 0.9653 | 780 | 0.2944 | 0.8625 | 0.8413 | 0.6285 | 0.7195 |
0.2252 | 0.9901 | 800 | 0.2939 | 0.8636 | 0.8421 | 0.6324 | 0.7223 |
Framework versions
- PEFT 0.13.2
- Transformers 4.46.0
- Pytorch 2.5.1+cu124
- Datasets 3.1.0
- Tokenizers 0.20.3
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Model tree for mtzig/v3c_mistral_lora
Base model
peiyi9979/math-shepherd-mistral-7b-prm