File size: 1,763 Bytes
5d9584e d1faa3b 5d9584e 3491e56 d1faa3b 5d9584e 3491e56 5d9584e a1999a8 3491e56 5d9584e d1faa3b 3491e56 5d9584e d1faa3b 5d9584e 99b0d21 5d9584e 3491e56 d8cc25f |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 |
---
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: wav2vec2-large-asr-th
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# wav2vec2-large-asr-th
This model was trained from scratch on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4214
- Wer: 0.3708
- Cer: 0.1236
## 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: 0.0002
- train_batch_size: 24
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 48
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- training_steps: 3000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
| 0.6395 | 0.86 | 500 | 0.5238 | 0.4279 | 0.1463 |
| 0.4942 | 1.71 | 1000 | 0.5227 | 0.4188 | 0.1404 |
| 0.4195 | 2.57 | 1500 | 0.4984 | 0.4019 | 0.1344 |
| 0.514 | 3.42 | 2000 | 0.4713 | 0.3828 | 0.1305 |
| 0.4964 | 4.28 | 2500 | 0.4490 | 0.3780 | 0.1261 |
| 0.5175 | 5.14 | 3000 | 0.4214 | 0.3708 | 0.1236 |
### Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2
|