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---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- common_voice
model-index:
- name: wav2vec2-large-xls-r-2b-armenian-colab
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-xls-r-2b-armenian-colab
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-2b](https://huggingface.co/facebook/wav2vec2-xls-r-2b) on the common_voice dataset.
It achieves the following results on the evaluation set:
- Loss: 1.5166
- Wer: 0.7397
## 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: 1
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 120
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:------:|:-----:|:---------------:|:------:|
| 3.7057 | 2.38 | 200 | 0.7731 | 0.8091 |
| 0.5797 | 4.76 | 400 | 0.8279 | 0.7804 |
| 0.4341 | 7.14 | 600 | 1.0343 | 0.8285 |
| 0.3135 | 9.52 | 800 | 1.0551 | 0.8066 |
| 0.2409 | 11.9 | 1000 | 1.0686 | 0.7897 |
| 0.1998 | 14.29 | 1200 | 1.1329 | 0.7766 |
| 0.1729 | 16.67 | 1400 | 1.3234 | 0.8567 |
| 0.1533 | 19.05 | 1600 | 1.2432 | 0.8160 |
| 0.1354 | 21.43 | 1800 | 1.2780 | 0.7954 |
| 0.12 | 23.81 | 2000 | 1.2228 | 0.8054 |
| 0.1175 | 26.19 | 2200 | 1.3484 | 0.8129 |
| 0.1141 | 28.57 | 2400 | 1.2881 | 0.9130 |
| 0.1053 | 30.95 | 2600 | 1.1972 | 0.7910 |
| 0.0954 | 33.33 | 2800 | 1.3702 | 0.8048 |
| 0.0842 | 35.71 | 3000 | 1.3963 | 0.7960 |
| 0.0793 | 38.1 | 3200 | 1.4690 | 0.7991 |
| 0.0707 | 40.48 | 3400 | 1.5045 | 0.8085 |
| 0.0745 | 42.86 | 3600 | 1.4749 | 0.8004 |
| 0.0693 | 45.24 | 3800 | 1.5047 | 0.7960 |
| 0.0646 | 47.62 | 4000 | 1.4216 | 0.7997 |
| 0.0555 | 50.0 | 4200 | 1.4676 | 0.8029 |
| 0.056 | 52.38 | 4400 | 1.4273 | 0.8104 |
| 0.0465 | 54.76 | 4600 | 1.3999 | 0.7841 |
| 0.046 | 57.14 | 4800 | 1.6130 | 0.8473 |
| 0.0404 | 59.52 | 5000 | 1.5586 | 0.7841 |
| 0.0403 | 61.9 | 5200 | 1.3959 | 0.7653 |
| 0.0404 | 64.29 | 5400 | 1.5318 | 0.8041 |
| 0.0365 | 66.67 | 5600 | 1.5300 | 0.7854 |
| 0.0338 | 69.05 | 5800 | 1.5051 | 0.7885 |
| 0.0307 | 71.43 | 6000 | 1.5647 | 0.7935 |
| 0.0235 | 73.81 | 6200 | 1.4919 | 0.8154 |
| 0.0268 | 76.19 | 6400 | 1.5259 | 0.8060 |
| 0.0275 | 78.57 | 6600 | 1.3985 | 0.7897 |
| 0.022 | 80.95 | 6800 | 1.5515 | 0.8154 |
| 0.017 | 83.33 | 7000 | 1.5737 | 0.7647 |
| 0.0205 | 85.71 | 7200 | 1.4876 | 0.7572 |
| 0.0174 | 88.1 | 7400 | 1.6331 | 0.7829 |
| 0.0188 | 90.48 | 7600 | 1.5108 | 0.7685 |
| 0.0134 | 92.86 | 7800 | 1.7125 | 0.7866 |
| 0.0125 | 95.24 | 8000 | 1.6042 | 0.7635 |
| 0.0133 | 97.62 | 8200 | 1.4608 | 0.7478 |
| 0.0272 | 100.0 | 8400 | 1.4784 | 0.7309 |
| 0.0133 | 102.38 | 8600 | 1.4471 | 0.7459 |
| 0.0094 | 104.76 | 8800 | 1.4852 | 0.7272 |
| 0.0103 | 107.14 | 9000 | 1.5679 | 0.7409 |
| 0.0088 | 109.52 | 9200 | 1.5090 | 0.7309 |
| 0.0077 | 111.9 | 9400 | 1.4994 | 0.7290 |
| 0.0068 | 114.29 | 9600 | 1.5008 | 0.7340 |
| 0.0054 | 116.67 | 9800 | 1.5166 | 0.7390 |
| 0.0052 | 119.05 | 10000 | 1.5166 | 0.7397 |
### Framework versions
- Transformers 4.14.1
- Pytorch 1.10.0
- Datasets 1.16.1
- Tokenizers 0.10.3
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