metadata
license: mit
base_model: facebook/w2v-bert-2.0
tags:
- generated_from_trainer
datasets:
- fleurs
metrics:
- wer
model-index:
- name: w2v-bert2-pashto-augmented
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: fleurs
type: fleurs
config: ps_af
split: test
args: ps_af
metrics:
- name: Wer
type: wer
value: 0.34313876482365624
w2v-bert2-pashto-augmented
This model is a fine-tuned version of facebook/w2v-bert-2.0 on the fleurs dataset. It achieves the following results on the evaluation set:
- Loss: 0.5954
- Wer: 0.3431
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: 5e-05
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 8
- 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
- training_steps: 700
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 3.0422 | 1.1713 | 100 | 3.0380 | 0.9640 |
| 2.3141 | 2.3426 | 200 | 2.0336 | 0.9464 |
| 0.7365 | 3.5139 | 300 | 0.6768 | 0.4520 |
| 0.557 | 4.6852 | 400 | 0.6051 | 0.3913 |
| 0.5101 | 5.8565 | 500 | 0.6571 | 0.3853 |
| 0.3803 | 7.0278 | 600 | 0.5946 | 0.3497 |
| 0.2452 | 8.1991 | 700 | 0.5954 | 0.3431 |
Framework versions
- Transformers 4.40.2
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1