|
--- |
|
base_model: ylacombe/w2v-bert-2.0 |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- common_voice_16_0 |
|
metrics: |
|
- wer |
|
model-index: |
|
- name: wav2vec2-common_voice-tr-demo |
|
results: |
|
- task: |
|
name: Automatic Speech Recognition |
|
type: automatic-speech-recognition |
|
dataset: |
|
name: common_voice_16_0 |
|
type: common_voice_16_0 |
|
config: tr |
|
split: test |
|
args: tr |
|
metrics: |
|
- name: Wer |
|
type: wer |
|
value: 1.0 |
|
--- |
|
|
|
<!-- 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-common_voice-tr-demo |
|
|
|
This model is a fine-tuned version of [ylacombe/w2v-bert-2.0](https://huggingface.co/ylacombe/w2v-bert-2.0) on the common_voice_16_0 dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 3.0815 |
|
- Wer: 1.0 |
|
|
|
## 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: 0.00072018208512399 |
|
- train_batch_size: 20 |
|
- eval_batch_size: 32 |
|
- seed: 42 |
|
- gradient_accumulation_steps: 2 |
|
- total_train_batch_size: 40 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- lr_scheduler_warmup_steps: 5000 |
|
- num_epochs: 15.0 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Wer | |
|
|:-------------:|:-----:|:-----:|:---------------:|:------:| |
|
| No log | 0.27 | 300 | 7.2663 | 1.0 | |
|
| 10.5256 | 0.55 | 600 | 3.0893 | 1.0 | |
|
| 10.5256 | 0.82 | 900 | 3.0612 | 1.0 | |
|
| 2.9795 | 1.1 | 1200 | 2.9937 | 1.0 | |
|
| 2.9564 | 1.37 | 1500 | 3.2424 | 1.0 | |
|
| 2.9564 | 1.64 | 1800 | 3.2866 | 1.0 | |
|
| 3.1552 | 1.92 | 2100 | 3.6339 | 1.0 | |
|
| 3.1552 | 2.19 | 2400 | 3.1185 | 1.0 | |
|
| 3.2079 | 2.47 | 2700 | 3.1832 | 1.0 | |
|
| 3.1275 | 2.74 | 3000 | 3.3952 | 1.0 | |
|
| 3.1275 | 3.01 | 3300 | 3.2982 | 1.0 | |
|
| 3.0987 | 3.29 | 3600 | 3.1036 | 1.0 | |
|
| 3.0987 | 3.56 | 3900 | 3.1223 | 1.0 | |
|
| 2.9301 | 3.84 | 4200 | 3.1145 | 1.0 | |
|
| 2.9197 | 4.11 | 4500 | 3.0324 | 1.0 | |
|
| 2.9197 | 4.38 | 4800 | 2.9994 | 1.9599 | |
|
| 2.9023 | 4.66 | 5100 | 2.9917 | 1.8240 | |
|
| 2.9023 | 4.93 | 5400 | 2.9946 | 1.9589 | |
|
| 2.9007 | 5.21 | 5700 | 3.1955 | 1.0 | |
|
| 3.1887 | 5.48 | 6000 | 3.1902 | 1.0 | |
|
| 3.1887 | 5.75 | 6300 | 3.1672 | 1.0 | |
|
| 3.135 | 6.03 | 6600 | 3.2076 | 1.0 | |
|
| 3.135 | 6.3 | 6900 | 3.2120 | 1.0 | |
|
| 3.1482 | 6.58 | 7200 | 3.1832 | 1.0 | |
|
| 3.1546 | 6.85 | 7500 | 3.1799 | 1.0 | |
|
| 3.1546 | 7.12 | 7800 | 3.2452 | 1.0 | |
|
| 3.1567 | 7.4 | 8100 | 3.2319 | 1.0 | |
|
| 3.1567 | 7.67 | 8400 | 3.2228 | 1.0 | |
|
| 3.1719 | 7.95 | 8700 | 3.2055 | 1.0 | |
|
| 3.168 | 8.22 | 9000 | 3.2553 | 1.0 | |
|
| 3.168 | 8.49 | 9300 | 3.1975 | 1.0 | |
|
| 3.1643 | 8.77 | 9600 | 3.2446 | 1.0 | |
|
| 3.1643 | 9.04 | 9900 | 3.2781 | 1.0 | |
|
| 3.169 | 9.32 | 10200 | 3.2597 | 1.0 | |
|
| 3.1789 | 9.59 | 10500 | 3.2586 | 1.0 | |
|
| 3.1789 | 9.86 | 10800 | 3.2690 | 1.0 | |
|
| 3.1701 | 10.14 | 11100 | 3.2737 | 1.0 | |
|
| 3.1701 | 10.41 | 11400 | 3.2738 | 1.0 | |
|
| 3.1698 | 10.68 | 11700 | 3.2595 | 1.0 | |
|
| 3.1595 | 10.96 | 12000 | 3.2467 | 1.0 | |
|
| 3.1595 | 11.23 | 12300 | 3.2524 | 1.0 | |
|
| 3.15 | 11.51 | 12600 | 3.2327 | 1.0 | |
|
| 3.15 | 11.78 | 12900 | 3.2196 | 1.0 | |
|
| 3.1444 | 12.05 | 13200 | 3.1943 | 1.0 | |
|
| 3.132 | 12.33 | 13500 | 3.1911 | 1.0 | |
|
| 3.132 | 12.6 | 13800 | 3.2075 | 1.0 | |
|
| 3.1153 | 12.88 | 14100 | 3.1938 | 1.0 | |
|
| 3.1153 | 13.15 | 14400 | 3.1639 | 1.0 | |
|
| 3.1039 | 13.42 | 14700 | 3.1515 | 1.0 | |
|
| 3.0839 | 13.7 | 15000 | 3.1535 | 1.0 | |
|
| 3.0839 | 13.97 | 15300 | 3.1307 | 1.0 | |
|
| 3.0632 | 14.25 | 15600 | 3.1138 | 1.0 | |
|
| 3.0632 | 14.52 | 15900 | 3.1289 | 1.0 | |
|
| 3.0518 | 14.79 | 16200 | 3.0815 | 1.0 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.37.0.dev0 |
|
- Pytorch 2.1.0+cu121 |
|
- Datasets 2.14.5 |
|
- Tokenizers 0.15.0 |
|
|
