llama3_darulm_20_05_24_part1-2_128000_unigram_part1_lr5e5_bs256
This model is a fine-tuned version of RefalMachine/llama3_darulm_20_05_24_part1-2_128000_unigram_mean_init_03_07_24 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 2.6592
- Accuracy: 0.4871
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 |
---|---|---|---|---|
3.0673 | 0.1 | 2000 | 2.8405 | 0.4694 |
2.959 | 0.2 | 4000 | 2.7320 | 0.4793 |
2.8963 | 0.3 | 6000 | 2.6919 | 0.4830 |
2.8852 | 0.4 | 8000 | 2.6741 | 0.4853 |
2.9148 | 0.5 | 10000 | 2.6655 | 0.4863 |
2.915 | 0.6 | 12000 | 2.6614 | 0.4868 |
2.9083 | 0.71 | 14000 | 2.6598 | 0.4871 |
2.8597 | 0.81 | 16000 | 2.6593 | 0.4872 |
2.8806 | 0.91 | 18000 | 2.6592 | 0.4870 |
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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