gpt-neo-vi-small-v6
This model is a fine-tuned version of NlpHUST/gpt-neo-vi-small on an ViQuad dataset. It achieves the following results on the evaluation set:
- Loss: 0.4156
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: 0.0003
- train_batch_size: 2
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 64
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 1
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
0.3849 | 0.1 | 25 | 0.5802 |
0.3747 | 0.19 | 50 | 0.5680 |
0.3843 | 0.29 | 75 | 0.5695 |
0.4016 | 0.39 | 100 | 0.5782 |
0.4101 | 0.49 | 125 | 0.5563 |
0.4011 | 0.58 | 150 | 0.5162 |
0.3729 | 0.68 | 175 | 0.4888 |
0.3512 | 0.78 | 200 | 0.4544 |
0.316 | 0.88 | 225 | 0.4319 |
0.3126 | 0.97 | 250 | 0.4156 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
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