HintsGenerator
This model is a fine-tuned version of t5-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.7541
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: 64
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 2.2228 | 1.0 | 1053 | 1.8560 |
| 2.078 | 2.0 | 2106 | 1.7876 |
| 1.9936 | 3.0 | 3159 | 1.7681 |
| 1.9479 | 4.0 | 4212 | 1.7580 |
| 1.911 | 5.0 | 5265 | 1.7552 |
| 1.883 | 6.0 | 6318 | 1.7642 |
| 1.8738 | 7.0 | 7371 | 1.7618 |
| 1.8524 | 8.0 | 8424 | 1.7571 |
| 1.847 | 9.0 | 9477 | 1.7532 |
| 1.8346 | 10.0 | 10530 | 1.7541 |
Framework versions
- Transformers 4.30.1
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
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# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("vishnun/HintsGenerator") model = AutoModelForSeq2SeqLM.from_pretrained("vishnun/HintsGenerator")