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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-v2
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-v2
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: 0.6293
- Model Preparation Time: 0.004
- Wer: 0.3558
- Cer: 0.1353
## 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: 0.0007
- train_batch_size: 32
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.6
- num_epochs: 120
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Model Preparation Time | Wer | Cer |
|:-------------:|:-----:|:-----:|:---------------:|:----------------------:|:------:|:------:|
| 3.5004 | 1.0 | 1040 | 0.7862 | 0.004 | 0.6822 | 0.1909 |
| 0.4704 | 2.0 | 2080 | 0.5245 | 0.004 | 0.4970 | 0.1335 |
| 0.3202 | 3.0 | 3120 | 0.4288 | 0.004 | 0.3956 | 0.1066 |
| 0.2551 | 4.0 | 4160 | 0.3800 | 0.004 | 0.3644 | 0.0962 |
| 0.2213 | 5.0 | 5200 | 0.3481 | 0.004 | 0.3358 | 0.0911 |
| 0.2005 | 6.0 | 6240 | 0.3241 | 0.004 | 0.3101 | 0.0839 |
| 0.1911 | 7.0 | 7280 | 0.3535 | 0.004 | 0.3283 | 0.0924 |
| 0.1854 | 8.0 | 8320 | 0.3161 | 0.004 | 0.3002 | 0.0843 |
| 0.1819 | 9.0 | 9360 | 0.3181 | 0.004 | 0.3233 | 0.0964 |
| 0.1788 | 10.0 | 10400 | 0.3099 | 0.004 | 0.3086 | 0.0832 |
| 0.1796 | 11.0 | 11440 | 0.3245 | 0.004 | 0.3011 | 0.0827 |
| 0.1805 | 12.0 | 12480 | 0.3068 | 0.004 | 0.2967 | 0.0845 |
| 0.1791 | 13.0 | 13520 | 0.3163 | 0.004 | 0.3076 | 0.0864 |
| 0.1812 | 14.0 | 14560 | 0.3336 | 0.004 | 0.3104 | 0.0867 |
| 0.1844 | 15.0 | 15600 | 0.3257 | 0.004 | 0.3117 | 0.0864 |
| 0.1884 | 16.0 | 16640 | 0.3440 | 0.004 | 0.3136 | 0.0886 |
| 0.1979 | 17.0 | 17680 | 0.3444 | 0.004 | 0.3172 | 0.0899 |
| 0.2058 | 18.0 | 18720 | 0.3286 | 0.004 | 0.3456 | 0.1092 |
| 0.2114 | 19.0 | 19760 | 0.3603 | 0.004 | 0.3358 | 0.0969 |
| 0.2229 | 20.0 | 20800 | 0.3658 | 0.004 | 0.3301 | 0.0954 |
| 0.2275 | 21.0 | 21840 | 0.3849 | 0.004 | 0.3729 | 0.1197 |
| 0.2351 | 22.0 | 22880 | 0.3753 | 0.004 | 0.3488 | 0.1011 |
### Framework versions
- Transformers 4.44.0
- Pytorch 2.1.0+cu118
- Datasets 2.20.0
- Tokenizers 0.19.1
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