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---
library_name: transformers
license: apache-2.0
base_model: facebook/wav2vec2-xls-r-1b
tags:
- generated_from_trainer
model-index:
- name: wav2vec2-1b-E50_speed2
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-E50_speed2
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: 0.7405
- Cer: 24.6417
## 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 |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 26.7947 | 0.2580 | 200 | 30.8746 | 111.8127 |
| 7.993 | 0.5160 | 400 | 5.7855 | 94.2317 |
| 4.7455 | 0.7741 | 600 | 4.5989 | 93.9262 |
| 4.4924 | 1.0321 | 800 | 4.7152 | 93.2331 |
| 4.3711 | 1.2901 | 1000 | 4.7883 | 93.3564 |
| 4.3243 | 1.5481 | 1200 | 4.7205 | 92.4636 |
| 4.2683 | 1.8062 | 1400 | 4.5020 | 90.9305 |
| 4.1967 | 2.0642 | 1600 | 4.8431 | 92.8102 |
| 4.0612 | 2.3222 | 1800 | 4.8480 | 92.2697 |
| 3.6744 | 2.5802 | 2000 | 3.8378 | 77.9664 |
| 2.8934 | 2.8383 | 2200 | 2.9635 | 61.9713 |
| 2.1459 | 3.0963 | 2400 | 2.1180 | 51.9267 |
| 1.5896 | 3.3543 | 2600 | 1.5030 | 38.3870 |
| 1.0885 | 3.6123 | 2800 | 1.1457 | 30.6978 |
| 0.8797 | 3.8703 | 3000 | 0.9902 | 29.2234 |
| 0.7317 | 4.1284 | 3200 | 0.8634 | 25.7636 |
| 0.6046 | 4.3864 | 3400 | 0.7911 | 24.6476 |
| 0.5618 | 4.6444 | 3600 | 0.7773 | 25.6285 |
| 0.5027 | 4.9024 | 3800 | 0.7405 | 24.6417 |
### Framework versions
- Transformers 4.45.2
- Pytorch 2.3.1.post100
- Datasets 2.19.1
- Tokenizers 0.20.1
|