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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-E30_freq
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-E30_freq
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: 0.4977
- Cer: 13.7277
## 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 |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 13.4278 | 0.2580 | 200 | 4.0083 | 87.1123 |
| 2.1559 | 0.5160 | 400 | 1.8970 | 40.9833 |
| 1.3277 | 0.7741 | 600 | 1.2101 | 31.0620 |
| 1.162 | 1.0321 | 800 | 1.0824 | 26.5096 |
| 0.9949 | 1.2901 | 1000 | 0.9657 | 24.2246 |
| 0.9109 | 1.5481 | 1200 | 1.0152 | 24.8414 |
| 0.8943 | 1.8062 | 1400 | 0.8544 | 21.7869 |
| 0.7895 | 2.0642 | 1600 | 0.9202 | 22.9617 |
| 0.6679 | 2.3222 | 1800 | 0.9574 | 24.1835 |
| 0.6296 | 2.5802 | 2000 | 0.7541 | 19.2199 |
| 0.6245 | 2.8383 | 2200 | 0.7259 | 19.2728 |
| 0.5656 | 3.0963 | 2400 | 0.6447 | 17.3344 |
| 0.4821 | 3.3543 | 2600 | 0.6489 | 16.9878 |
| 0.4513 | 3.6123 | 2800 | 0.6556 | 17.5282 |
| 0.4285 | 3.8703 | 3000 | 0.6180 | 16.7234 |
| 0.374 | 4.1284 | 3200 | 0.5651 | 15.2314 |
| 0.3375 | 4.3864 | 3400 | 0.5135 | 13.8275 |
| 0.3158 | 4.6444 | 3600 | 0.4945 | 13.7688 |
| 0.2897 | 4.9024 | 3800 | 0.4977 | 13.7277 |
### Framework versions
- Transformers 4.45.2
- Pytorch 2.3.1.post100
- Datasets 2.19.1
- Tokenizers 0.20.1
|