mistral_darulm_20_05_24_part1-2_32000_unigram_part1_lr1e4_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: 2.0924
- Accuracy: 0.5528
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: 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 |
---|---|---|---|---|
2.4483 | 0.09 | 2000 | 2.2346 | 0.5327 |
2.3981 | 0.18 | 4000 | 2.1935 | 0.5381 |
2.3458 | 0.26 | 6000 | 2.1723 | 0.5408 |
2.3539 | 0.35 | 8000 | 2.1518 | 0.5437 |
2.3637 | 0.44 | 10000 | 2.1349 | 0.5463 |
2.3438 | 0.53 | 12000 | 2.1194 | 0.5487 |
2.283 | 0.61 | 14000 | 2.1059 | 0.5507 |
2.3057 | 0.7 | 16000 | 2.0977 | 0.5520 |
2.2765 | 0.79 | 18000 | 2.0937 | 0.5526 |
2.2652 | 0.88 | 20000 | 2.0925 | 0.5528 |
2.2647 | 0.96 | 22000 | 2.0924 | 0.5529 |
Framework versions
- Transformers 4.37.2
- Pytorch 2.3.0a0+6ddf5cf85e.nv24.04
- Datasets 2.18.0
- Tokenizers 0.15.2
- Downloads last month
- 2
Inference Providers
NEW
This model isn't deployed by any Inference Provider.
๐
Ask for provider support