|
--- |
|
library_name: transformers |
|
license: apache-2.0 |
|
base_model: facebook/wav2vec2-xls-r-1b |
|
tags: |
|
- generated_from_trainer |
|
model-index: |
|
- name: wav2vec2-1b-E30_freq |
|
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. --> |
|
|
|
# wav2vec2-1b-E30_freq |
|
|
|
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-1b](https://huggingface.co/facebook/wav2vec2-xls-r-1b) on an unknown dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.4977 |
|
- Cer: 13.7277 |
|
|
|
## 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: 2 |
|
- eval_batch_size: 8 |
|
- seed: 42 |
|
- gradient_accumulation_steps: 8 |
|
- total_train_batch_size: 16 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- lr_scheduler_warmup_steps: 50 |
|
- num_epochs: 5 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Cer | |
|
|:-------------:|:------:|:----:|:---------------:|:-------:| |
|
| 13.4278 | 0.2580 | 200 | 4.0083 | 87.1123 | |
|
| 2.1559 | 0.5160 | 400 | 1.8970 | 40.9833 | |
|
| 1.3277 | 0.7741 | 600 | 1.2101 | 31.0620 | |
|
| 1.162 | 1.0321 | 800 | 1.0824 | 26.5096 | |
|
| 0.9949 | 1.2901 | 1000 | 0.9657 | 24.2246 | |
|
| 0.9109 | 1.5481 | 1200 | 1.0152 | 24.8414 | |
|
| 0.8943 | 1.8062 | 1400 | 0.8544 | 21.7869 | |
|
| 0.7895 | 2.0642 | 1600 | 0.9202 | 22.9617 | |
|
| 0.6679 | 2.3222 | 1800 | 0.9574 | 24.1835 | |
|
| 0.6296 | 2.5802 | 2000 | 0.7541 | 19.2199 | |
|
| 0.6245 | 2.8383 | 2200 | 0.7259 | 19.2728 | |
|
| 0.5656 | 3.0963 | 2400 | 0.6447 | 17.3344 | |
|
| 0.4821 | 3.3543 | 2600 | 0.6489 | 16.9878 | |
|
| 0.4513 | 3.6123 | 2800 | 0.6556 | 17.5282 | |
|
| 0.4285 | 3.8703 | 3000 | 0.6180 | 16.7234 | |
|
| 0.374 | 4.1284 | 3200 | 0.5651 | 15.2314 | |
|
| 0.3375 | 4.3864 | 3400 | 0.5135 | 13.8275 | |
|
| 0.3158 | 4.6444 | 3600 | 0.4945 | 13.7688 | |
|
| 0.2897 | 4.9024 | 3800 | 0.4977 | 13.7277 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.45.2 |
|
- Pytorch 2.3.1.post100 |
|
- Datasets 2.19.1 |
|
- Tokenizers 0.20.1 |
|
|