|
--- |
|
license: apache-2.0 |
|
base_model: facebook/wav2vec2-large-xlsr-53 |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- common_voice_16_1 |
|
metrics: |
|
- wer |
|
model-index: |
|
- name: wav2vec2-large-xls-r-300m-upper-sorbian-cz-frozen-2-colab |
|
results: |
|
- task: |
|
name: Automatic Speech Recognition |
|
type: automatic-speech-recognition |
|
dataset: |
|
name: common_voice_16_1 |
|
type: common_voice_16_1 |
|
config: hsb |
|
split: test |
|
args: hsb |
|
metrics: |
|
- name: Wer |
|
type: wer |
|
value: 0.4301780693533271 |
|
--- |
|
|
|
<!-- 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-xls-r-300m-upper-sorbian-cz-frozen-2-colab |
|
|
|
This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the common_voice_16_1 dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.7163 |
|
- Wer: 0.4302 |
|
- Cer: 0.1003 |
|
|
|
## 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: 16 |
|
- eval_batch_size: 8 |
|
- 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 |
|
- lr_scheduler_warmup_steps: 500 |
|
- num_epochs: 60 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer | |
|
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:| |
|
| 0.6172 | 3.23 | 100 | 0.6599 | 0.6999 | 0.1787 | |
|
| 0.4414 | 6.45 | 200 | 0.6030 | 0.6251 | 0.1524 | |
|
| 0.289 | 9.68 | 300 | 0.5899 | 0.5670 | 0.1336 | |
|
| 0.1953 | 12.9 | 400 | 0.6095 | 0.5457 | 0.1308 | |
|
| 0.1388 | 16.13 | 500 | 0.6628 | 0.5159 | 0.1224 | |
|
| 0.1187 | 19.35 | 600 | 0.7075 | 0.4932 | 0.1180 | |
|
| 0.0994 | 22.58 | 700 | 0.7131 | 0.4780 | 0.1143 | |
|
| 0.0816 | 25.81 | 800 | 0.6959 | 0.4752 | 0.1101 | |
|
| 0.0727 | 29.03 | 900 | 0.7201 | 0.4644 | 0.1104 | |
|
| 0.0637 | 32.26 | 1000 | 0.7288 | 0.4630 | 0.1080 | |
|
| 0.0592 | 35.48 | 1100 | 0.7219 | 0.4524 | 0.1056 | |
|
| 0.0549 | 38.71 | 1200 | 0.7204 | 0.4480 | 0.1041 | |
|
| 0.0473 | 41.94 | 1300 | 0.7238 | 0.4470 | 0.1048 | |
|
| 0.0412 | 45.16 | 1400 | 0.7109 | 0.4278 | 0.1011 | |
|
| 0.0423 | 48.39 | 1500 | 0.7252 | 0.4407 | 0.1045 | |
|
| 0.0419 | 51.61 | 1600 | 0.7193 | 0.4393 | 0.1028 | |
|
| 0.0365 | 54.84 | 1700 | 0.7231 | 0.4318 | 0.1010 | |
|
| 0.0347 | 58.06 | 1800 | 0.7163 | 0.4302 | 0.1003 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.38.2 |
|
- Pytorch 2.2.1+cu121 |
|
- Datasets 2.18.0 |
|
- Tokenizers 0.15.2 |
|
|
