EngToFil
This model is a fine-tuned version of t5-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.9377
- Bleu: 17.4001
- Gen Len: 17.2588
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: 0.002
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Bleu | Gen Len |
|---|---|---|---|---|---|
| 0.5791 | 1.0 | 2438 | 1.0743 | 12.9852 | 17.3555 |
| 0.3516 | 2.0 | 4876 | 0.9317 | 16.1227 | 17.3014 |
| 0.2143 | 3.0 | 7314 | 0.9377 | 17.4001 | 17.2588 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.1
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Base model
google-t5/t5-base
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("roval15/EngToFil") model = AutoModelForSeq2SeqLM.from_pretrained("roval15/EngToFil", device_map="auto")