File size: 2,218 Bytes
3dc87b3 |
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 70 71 72 73 |
---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: wav2vec2-xls-r-300m-th-v2
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-xls-r-300m-th-v2
This model is a fine-tuned version of [Botnoi/wav2vec2-xls-r-300m-th-v1](https://huggingface.co/Botnoi/wav2vec2-xls-r-300m-th-v1) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3630
- Wer: 0.3962
- Cer: 0.0942
- Clean Cer: 0.0767
## 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: 4.533e-08
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 9000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer | Clean Cer |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:---------:|
| 0.3323 | 0.68 | 1000 | 0.3635 | 0.3961 | 0.0942 | 0.0767 |
| 0.3386 | 1.36 | 2000 | 0.3632 | 0.3962 | 0.0943 | 0.0768 |
| 0.3453 | 2.03 | 3000 | 0.3632 | 0.3964 | 0.0943 | 0.0768 |
| 0.3392 | 2.71 | 4000 | 0.3632 | 0.3961 | 0.0943 | 0.0767 |
| 0.3399 | 3.39 | 5000 | 0.3634 | 0.3961 | 0.0942 | 0.0768 |
| 0.347 | 4.07 | 6000 | 0.3632 | 0.3961 | 0.0942 | 0.0767 |
| 0.3414 | 4.74 | 7000 | 0.3631 | 0.3962 | 0.0942 | 0.0767 |
| 0.3378 | 5.42 | 8000 | 0.3631 | 0.3961 | 0.0942 | 0.0767 |
| 0.3421 | 6.1 | 9000 | 0.3630 | 0.3962 | 0.0942 | 0.0767 |
### Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu116
- Datasets 2.8.0
- Tokenizers 0.13.2
|