seq2seq_huggingface_mix_results
This model is a fine-tuned version of on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 7.9457
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: 12
- eval_batch_size: 12
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 48
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 1
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
10.7021 | 0.0480 | 10 | 10.6458 |
10.5611 | 0.0959 | 20 | 10.4143 |
10.2935 | 0.1439 | 30 | 10.0786 |
9.9673 | 0.1918 | 40 | 9.7462 |
9.6468 | 0.2398 | 50 | 9.4724 |
9.4303 | 0.2878 | 60 | 9.2583 |
9.2452 | 0.3357 | 70 | 9.1136 |
9.1357 | 0.3837 | 80 | 9.0100 |
9.0307 | 0.4317 | 90 | 8.9296 |
8.9363 | 0.4796 | 100 | 8.8591 |
8.8781 | 0.5276 | 110 | 8.7821 |
8.7907 | 0.5755 | 120 | 8.7088 |
8.7214 | 0.6235 | 130 | 8.6329 |
8.6375 | 0.6715 | 140 | 8.5511 |
8.5439 | 0.7194 | 150 | 8.4701 |
8.4715 | 0.7674 | 160 | 8.3835 |
8.389 | 0.8153 | 170 | 8.2962 |
8.2787 | 0.8633 | 180 | 8.2072 |
8.1826 | 0.9113 | 190 | 8.1146 |
8.0848 | 0.9592 | 200 | 8.0225 |
Framework versions
- Transformers 4.40.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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