mistral_darulm_20_05_24_part1-2_32000_unigram_part1_lr5e5_bs256
This model is a fine-tuned version of RefalMachine/mistral_darulm_20_05_24_part1-2_32000_unigram_mean_init_03_07_24 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 2.1216
- Accuracy: 0.5495
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: 5e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 32
- total_train_batch_size: 128
- total_eval_batch_size: 128
- optimizer: Adam with betas=(0.9,0.95) and epsilon=1e-05
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 100
- num_epochs: 1.0
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
2.4577 | 0.09 | 2000 | 2.2397 | 0.5337 |
2.3958 | 0.18 | 4000 | 2.1904 | 0.5394 |
2.3424 | 0.26 | 6000 | 2.1684 | 0.5425 |
2.3564 | 0.35 | 8000 | 2.1525 | 0.5446 |
2.3706 | 0.44 | 10000 | 2.1411 | 0.5464 |
2.3589 | 0.53 | 12000 | 2.1325 | 0.5479 |
2.3058 | 0.61 | 14000 | 2.1263 | 0.5487 |
2.3347 | 0.7 | 16000 | 2.1234 | 0.5492 |
2.3072 | 0.79 | 18000 | 2.1220 | 0.5495 |
2.2975 | 0.88 | 20000 | 2.1217 | 0.5495 |
2.2975 | 0.96 | 22000 | 2.1216 | 0.5495 |
Framework versions
- Transformers 4.37.2
- Pytorch 2.3.0a0+6ddf5cf85e.nv24.04
- Datasets 2.18.0
- Tokenizers 0.15.2
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