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---
base_model: facebook/wav2vec2-large
license: apache-2.0
metrics:
- wer
tags:
- generated_from_trainer
model-index:
- name: wav2vec2-large-sw-cv-100hr-v3
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-large-sw-cv-100hr-v3
This model is a fine-tuned version of [facebook/wav2vec2-large](https://huggingface.co/facebook/wav2vec2-large) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.8721
- Model Preparation Time: 0.0042
- Wer: 0.9997
- Cer: 0.9176
## 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_ratio: 0.1
- num_epochs: 120
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Model Preparation Time | Wer | Cer |
|:-------------:|:-------:|:-----:|:---------------:|:----------------------:|:------:|:------:|
| 4.0159 | 0.9998 | 2079 | 2.7894 | 0.0042 | 0.9999 | 0.9048 |
| 2.8122 | 2.0 | 4159 | 2.8360 | 0.0042 | 1.0 | 1.0 |
| 2.8312 | 2.9998 | 6238 | 2.8331 | 0.0042 | 1.0 | 1.0 |
| 2.8295 | 4.0 | 8318 | 2.8340 | 0.0042 | 1.0 | 1.0 |
| 2.8306 | 4.9998 | 10397 | 2.8309 | 0.0042 | 1.0 | 1.0 |
| 2.8301 | 6.0 | 12477 | 2.8451 | 0.0042 | 1.0 | 1.0 |
| 2.8305 | 6.9998 | 14556 | 2.8320 | 0.0042 | 1.0 | 1.0 |
| 2.8547 | 8.0 | 16636 | 2.8626 | 0.0042 | 1.0 | 1.0 |
| 2.8611 | 8.9998 | 18715 | 2.8569 | 0.0042 | 1.0 | 1.0 |
| 2.8596 | 10.0 | 20795 | 2.8573 | 0.0042 | 1.0 | 1.0 |
| 2.861 | 10.9998 | 22874 | 2.8570 | 0.0042 | 1.0 | 1.0 |
### Framework versions
- Transformers 4.44.0
- Pytorch 2.1.0+cu118
- Datasets 2.20.0
- Tokenizers 0.19.1
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