|
--- |
|
license: apache-2.0 |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- openslr |
|
metrics: |
|
- wer |
|
model-index: |
|
- name: wav2vec2-telugu_150 |
|
results: |
|
- task: |
|
name: Automatic Speech Recognition |
|
type: automatic-speech-recognition |
|
dataset: |
|
name: openslr |
|
type: openslr |
|
config: SLR66 |
|
split: train |
|
args: SLR66 |
|
metrics: |
|
- name: Wer |
|
type: wer |
|
value: 0.2212659135736059 |
|
--- |
|
|
|
<!-- 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-telugu_150 |
|
|
|
This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the [openslr](https://openslr.org/66) dataset. |
|
|
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.3312 |
|
- Wer: 0.2213 |
|
|
|
|
|
### 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: 150 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Wer | |
|
|:-------------:|:------:|:-----:|:---------------:|:------:| |
|
| 6.096 | 3.84 | 400 | 0.5762 | 0.7029 | |
|
| 0.427 | 7.69 | 800 | 0.3124 | 0.5148 | |
|
| 0.208 | 11.54 | 1200 | 0.2994 | 0.4201 | |
|
| 0.1506 | 15.38 | 1600 | 0.3106 | 0.3844 | |
|
| 0.1223 | 19.23 | 2000 | 0.3080 | 0.3608 | |
|
| 0.1094 | 23.08 | 2400 | 0.3206 | 0.3332 | |
|
| 0.0949 | 26.92 | 2800 | 0.3085 | 0.3253 | |
|
| 0.0802 | 30.77 | 3200 | 0.3076 | 0.3425 | |
|
| 0.0713 | 34.61 | 3600 | 0.3280 | 0.3398 | |
|
| 0.0687 | 38.46 | 4000 | 0.3042 | 0.3081 | |
|
| 0.0613 | 42.31 | 4400 | 0.3227 | 0.3073 | |
|
| 0.0548 | 46.15 | 4800 | 0.3152 | 0.3213 | |
|
| 0.0508 | 50.0 | 5200 | 0.3259 | 0.3107 | |
|
| 0.0455 | 53.84 | 5600 | 0.3046 | 0.2881 | |
|
| 0.0427 | 57.69 | 6000 | 0.2779 | 0.3007 | |
|
| 0.0391 | 61.54 | 6400 | 0.2996 | 0.2693 | |
|
| 0.0388 | 65.38 | 6800 | 0.3016 | 0.2695 | |
|
| 0.0339 | 69.23 | 7200 | 0.3225 | 0.2935 | |
|
| 0.0312 | 73.08 | 7600 | 0.2907 | 0.2942 | |
|
| 0.029 | 76.92 | 8000 | 0.3148 | 0.3029 | |
|
| 0.0254 | 80.77 | 8400 | 0.3118 | 0.2996 | |
|
| 0.0229 | 84.61 | 8800 | 0.3022 | 0.2993 | |
|
| 0.0231 | 88.46 | 9200 | 0.3203 | 0.2465 | |
|
| 0.019 | 92.31 | 9600 | 0.3223 | 0.2460 | |
|
| 0.0173 | 96.15 | 10000 | 0.3178 | 0.2501 | |
|
| 0.0168 | 100.0 | 10400 | 0.2937 | 0.2415 | |
|
| 0.015 | 103.84 | 10800 | 0.3062 | 0.2415 | |
|
| 0.014 | 107.69 | 11200 | 0.3104 | 0.2383 | |
|
| 0.012 | 111.54 | 11600 | 0.3308 | 0.2408 | |
|
| 0.0111 | 115.38 | 12000 | 0.3228 | 0.2335 | |
|
| 0.01 | 119.23 | 12400 | 0.3228 | 0.2374 | |
|
| 0.0096 | 123.08 | 12800 | 0.3241 | 0.2304 | |
|
| 0.009 | 126.92 | 13200 | 0.3237 | 0.2295 | |
|
| 0.0075 | 130.77 | 13600 | 0.3221 | 0.2261 | |
|
| 0.0065 | 134.61 | 14000 | 0.3310 | 0.2277 | |
|
| 0.0064 | 138.46 | 14400 | 0.3348 | 0.2266 | |
|
| 0.0064 | 142.31 | 14800 | 0.3330 | 0.2229 | |
|
| 0.0056 | 146.15 | 15200 | 0.3310 | 0.2229 | |
|
| 0.0053 | 150.0 | 15600 | 0.3312 | 0.2213 | |
|
|
|
### Test results |
|
|
|
WER(without LM): 42.8\% |
|
|
|
WER(with LM): 42\% |
|
### Framework versions |
|
|
|
- Transformers 4.24.0 |
|
- Pytorch 1.13.0+cu117 |
|
- Datasets 2.6.1 |
|
- Tokenizers 0.13.2 |
|
|
|
ps: 150 in repo name denotes number of epochs |
