xls-r-es-test-lm-finetuned-sentiment-mesd
This model is a fine-tuned version of glob-asr/xls-r-es-test-lm on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.7851
- Accuracy: 0.2385
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1.25e-05
- train_batch_size: 64
- eval_batch_size: 40
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 256
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 20
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 0.86 | 3 | 1.7876 | 0.1923 |
| 1.9709 | 1.86 | 6 | 1.7869 | 0.2 |
| 1.9709 | 2.86 | 9 | 1.7859 | 0.2308 |
| 2.146 | 3.86 | 12 | 1.7851 | 0.2385 |
| 1.9622 | 4.86 | 15 | 1.7842 | 0.1923 |
| 1.9622 | 5.86 | 18 | 1.7834 | 0.1769 |
| 2.137 | 6.86 | 21 | 1.7823 | 0.1923 |
| 2.137 | 7.86 | 24 | 1.7812 | 0.1923 |
| 2.1297 | 8.86 | 27 | 1.7800 | 0.1846 |
| 1.9502 | 9.86 | 30 | 1.7787 | 0.1846 |
| 1.9502 | 10.86 | 33 | 1.7772 | 0.1846 |
| 2.1234 | 11.86 | 36 | 1.7760 | 0.1846 |
| 2.1234 | 12.86 | 39 | 1.7748 | 0.1846 |
| 2.1186 | 13.86 | 42 | 1.7736 | 0.1846 |
| 1.9401 | 14.86 | 45 | 1.7725 | 0.1846 |
| 1.9401 | 15.86 | 48 | 1.7715 | 0.1923 |
| 2.112 | 16.86 | 51 | 1.7706 | 0.1923 |
| 2.112 | 17.86 | 54 | 1.7701 | 0.1923 |
| 2.1094 | 18.86 | 57 | 1.7697 | 0.2 |
| 1.934 | 19.86 | 60 | 1.7696 | 0.2 |
Framework versions
- Transformers 4.17.0
- Pytorch 1.10.0+cu111
- Datasets 2.0.0
- Tokenizers 0.11.6