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18-24-finetuned-eng-to-para
This model is a fine-tuned version of Tri1/12-18-finetuned-eng-to-para on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.3257
- Bleu: 17.0341
- Gen Len: 24.16
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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 6
Training results
| Training Loss | Epoch | Step | Validation Loss | Bleu | Gen Len |
|---|---|---|---|---|---|
| 0.1696 | 1.0 | 6250 | 0.3216 | 18.5922 | 24.048 |
| 0.1554 | 2.0 | 12500 | 0.3225 | 17.7026 | 23.992 |
| 0.1474 | 3.0 | 18750 | 0.3242 | 17.2459 | 24.176 |
| 0.1387 | 4.0 | 25000 | 0.3243 | 17.3668 | 23.856 |
| 0.1314 | 5.0 | 31250 | 0.3247 | 17.4414 | 24.416 |
| 0.1277 | 6.0 | 37500 | 0.3257 | 17.0341 | 24.16 |
Framework versions
- Transformers 4.30.1
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.13.3
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# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Tri1/18-24-finetuned-eng-to-para") model = AutoModelForSeq2SeqLM.from_pretrained("Tri1/18-24-finetuned-eng-to-para", device_map="auto")