File size: 2,528 Bytes
d2fd4b2 bbd6e56 d2fd4b2 bbd6e56 d2fd4b2 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 |
---
library_name: transformers
license: apache-2.0
base_model: facebook/wav2vec2-xls-r-1b
tags:
- automatic-speech-recognition
- bemgen
- generated_from_trainer
metrics:
- wer
model-index:
- name: xls-r-1b-bemgen-male-model
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. -->
# xls-r-1b-bemgen-male-model
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-1b](https://huggingface.co/facebook/wav2vec2-xls-r-1b) on the BEMGEN - NA dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3453
- Wer: 0.4416
## 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: 3e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 30.0
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:------:|:----:|:---------------:|:------:|
| No log | 0.3604 | 100 | 3.5018 | 1.0 |
| No log | 0.7207 | 200 | 2.8616 | 1.0 |
| No log | 1.0793 | 300 | 1.1005 | 0.9874 |
| No log | 1.4396 | 400 | 0.6285 | 0.8360 |
| 5.4329 | 1.8 | 500 | 0.5177 | 0.7589 |
| 5.4329 | 2.1586 | 600 | 0.4120 | 0.5989 |
| 5.4329 | 2.5189 | 700 | 0.3998 | 0.5496 |
| 5.4329 | 2.8793 | 800 | 0.3715 | 0.5654 |
| 5.4329 | 3.2378 | 900 | 0.3351 | 0.4872 |
| 0.644 | 3.5982 | 1000 | 0.3334 | 0.5015 |
| 0.644 | 3.9586 | 1100 | 0.3192 | 0.4796 |
| 0.644 | 4.3171 | 1200 | 0.3246 | 0.4594 |
| 0.644 | 4.6775 | 1300 | 0.3242 | 0.4612 |
| 0.644 | 5.0360 | 1400 | 0.3203 | 0.4442 |
| 0.3852 | 5.3964 | 1500 | 0.3453 | 0.4416 |
### Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0
|