ruadapt_qwen2.5_3B_bpe_32000_full_lr2e4_bs256
This model is a fine-tuned version of RefalMachine/ruadapt_qwen2.5_3B_bpe_32000_mean_init on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 2.4027
- Accuracy: 0.5129
Model description
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Intended uses & limitations
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Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0002
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- distributed_type: multi-GPU
- num_devices: 64
- gradient_accumulation_steps: 2
- total_train_batch_size: 256
- 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 |
---|---|---|---|---|
No log | 0.0 | 1 | 5.9470 | 0.1656 |
2.563 | 0.16 | 2000 | 2.4362 | 0.5088 |
2.5528 | 0.32 | 4000 | 2.4107 | 0.5119 |
2.5219 | 0.48 | 6000 | 2.4048 | 0.5125 |
2.5339 | 0.65 | 8000 | 2.4030 | 0.5130 |
2.5223 | 0.81 | 10000 | 2.4027 | 0.5130 |
2.5186 | 0.97 | 12000 | 2.4026 | 0.5130 |
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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