|
--- |
|
base_model: ylacombe/w2v-bert-2.0 |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- common_voice_16_0 |
|
metrics: |
|
- wer |
|
model-index: |
|
- name: w2v-bert-2.0-600m-turkish-colab |
|
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: 0.13727393664832993 |
|
--- |
|
|
|
<!-- 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. --> |
|
|
|
# w2v-bert-2.0-600m-turkish-colab |
|
|
|
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: 0.1441 |
|
- Wer: 0.1373 |
|
|
|
## 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: 0.0001 |
|
- 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: 1000 |
|
- num_epochs: 5 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Wer | |
|
|:-------------:|:-----:|:----:|:---------------:|:------:| |
|
| 0.252 | 0.29 | 400 | 0.3121 | 0.3150 | |
|
| 0.2541 | 0.58 | 800 | 0.3786 | 0.3441 | |
|
| 0.2505 | 0.88 | 1200 | 0.4106 | 0.3766 | |
|
| 0.1958 | 1.17 | 1600 | 0.2974 | 0.2877 | |
|
| 0.1686 | 1.46 | 2000 | 0.2854 | 0.2736 | |
|
| 0.1498 | 1.75 | 2400 | 0.2508 | 0.2486 | |
|
| 0.1343 | 2.05 | 2800 | 0.2315 | 0.2263 | |
|
| 0.1045 | 2.34 | 3200 | 0.2207 | 0.2243 | |
|
| 0.0983 | 2.63 | 3600 | 0.2109 | 0.2046 | |
|
| 0.089 | 2.92 | 4000 | 0.1970 | 0.1896 | |
|
| 0.0726 | 3.21 | 4400 | 0.1963 | 0.1799 | |
|
| 0.0552 | 3.51 | 4800 | 0.1879 | 0.1778 | |
|
| 0.0573 | 3.8 | 5200 | 0.1821 | 0.1693 | |
|
| 0.0421 | 4.09 | 5600 | 0.1602 | 0.1517 | |
|
| 0.0363 | 4.38 | 6000 | 0.1564 | 0.1485 | |
|
| 0.0345 | 4.67 | 6400 | 0.1466 | 0.1437 | |
|
| 0.0294 | 4.97 | 6800 | 0.1441 | 0.1373 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.37.0.dev0 |
|
- Pytorch 2.1.0+cu121 |
|
- Datasets 2.16.1 |
|
- Tokenizers 0.15.0 |
|
|
