Instructions to use mamlong34/t5_small_race_mutlirc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mamlong34/t5_small_race_mutlirc with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("mamlong34/t5_small_race_mutlirc") model = AutoModelForSeq2SeqLM.from_pretrained("mamlong34/t5_small_race_mutlirc") - Notebooks
- Google Colab
- Kaggle
| { | |
| "epoch": 3.0, | |
| "eval_accuracy": 0.5259, | |
| "eval_loss": 0.5759526491165161, | |
| "eval_runtime": 306.5639, | |
| "eval_samples": 7872, | |
| "eval_samples_per_second": 25.678, | |
| "eval_steps_per_second": 1.605, | |
| "predict_accuracy": 0.2201, | |
| "predict_loss": 3.6130311489105225, | |
| "predict_runtime": 460.6956, | |
| "predict_samples": 11897, | |
| "predict_samples_per_second": 25.824, | |
| "predict_steps_per_second": 1.615, | |
| "train_loss": 0.05477445060331273, | |
| "train_runtime": 3408.5838, | |
| "train_samples": 113128, | |
| "train_samples_per_second": 99.567, | |
| "train_steps_per_second": 12.446 | |
| } |