metadata
library_name: transformers
license: apache-2.0
base_model: facebook/wav2vec2-xls-r-1b
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: wav2vec2-xslr-tr-testv2
results: []
wav2vec2-xslr-tr-testv2
This model is a fine-tuned version of facebook/wav2vec2-xls-r-1b on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.2789
- Wer: 0.4783
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: 0.0003
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 5.0
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| No log | 0.1375 | 100 | 2.9646 | 1.0 |
| No log | 0.2749 | 200 | 0.9689 | 0.9848 |
| No log | 0.4124 | 300 | 0.8561 | 0.9170 |
| No log | 0.5498 | 400 | 0.7970 | 0.912 |
| 1.9898 | 0.6873 | 500 | 0.8464 | 0.9258 |
| 1.9898 | 0.8247 | 600 | 0.7358 | 0.8872 |
| 1.9898 | 0.9622 | 700 | 0.6374 | 0.8608 |
| 1.9898 | 1.0997 | 800 | 0.5180 | 0.7297 |
| 1.9898 | 1.2371 | 900 | 0.4852 | 0.7212 |
| 0.663 | 1.3746 | 1000 | 0.4840 | 0.7278 |
| 0.663 | 1.5120 | 1100 | 0.4626 | 0.7135 |
| 0.663 | 1.6495 | 1200 | 0.4493 | 0.676 |
| 0.663 | 1.7869 | 1300 | 0.4419 | 0.6813 |
| 0.663 | 1.9244 | 1400 | 0.4306 | 0.6749 |
| 0.5455 | 2.0619 | 1500 | 0.4329 | 0.6846 |
| 0.5455 | 2.1993 | 1600 | 0.4227 | 0.6685 |
| 0.5455 | 2.3368 | 1700 | 0.4097 | 0.6472 |
| 0.5455 | 2.4742 | 1800 | 0.4035 | 0.6343 |
| 0.5455 | 2.6117 | 1900 | 0.4041 | 0.6304 |
| 0.433 | 2.7491 | 2000 | 0.3962 | 0.6542 |
| 0.433 | 2.8866 | 2100 | 0.3601 | 0.6041 |
| 0.433 | 3.0241 | 2200 | 0.3473 | 0.5864 |
| 0.433 | 3.1615 | 2300 | 0.3456 | 0.5723 |
| 0.433 | 3.2990 | 2400 | 0.3380 | 0.5617 |
| 0.3509 | 3.4364 | 2500 | 0.3267 | 0.5563 |
| 0.3509 | 3.5739 | 2600 | 0.3208 | 0.5570 |
| 0.3509 | 3.7113 | 2700 | 0.3124 | 0.5397 |
| 0.3509 | 3.8488 | 2800 | 0.3038 | 0.5272 |
| 0.3509 | 3.9863 | 2900 | 0.2994 | 0.5254 |
| 0.2871 | 4.1237 | 3000 | 0.3073 | 0.5247 |
| 0.2871 | 4.2612 | 3100 | 0.3009 | 0.5122 |
| 0.2871 | 4.3986 | 3200 | 0.2975 | 0.4953 |
| 0.2871 | 4.5361 | 3300 | 0.2898 | 0.4938 |
| 0.2871 | 4.6735 | 3400 | 0.2835 | 0.4902 |
| 0.2198 | 4.8110 | 3500 | 0.2804 | 0.4802 |
| 0.2198 | 4.9485 | 3600 | 0.2789 | 0.4783 |
Framework versions
- Transformers 4.46.0.dev0
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.20.0