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---
license: cc-by-nc-4.0
base_model: facebook/mms-1b-all
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: wav2vec2-large-mms-1b-tira-lid
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-mms-1b-tira-lid
This model is a fine-tuned version of [facebook/mms-1b-all](https://huggingface.co/facebook/mms-1b-all) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0026
- Accuracy: 1.0
## 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: 0.001
- train_batch_size: 1
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- total_train_batch_size: 2
- total_eval_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 4
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.3168 | 0.42 | 100 | 0.2023 | 0.9167 |
| 0.3278 | 0.84 | 200 | 0.1465 | 0.9667 |
| 0.2725 | 1.26 | 300 | 0.6432 | 0.8 |
| 0.1371 | 1.67 | 400 | 0.0144 | 1.0 |
| 0.094 | 2.09 | 500 | 0.0015 | 1.0 |
| 0.0654 | 2.51 | 600 | 0.0978 | 0.9667 |
| 0.1813 | 2.93 | 700 | 0.1174 | 0.9833 |
| 0.032 | 3.35 | 800 | 0.0019 | 1.0 |
| 0.0422 | 3.77 | 900 | 0.0026 | 1.0 |
### Framework versions
- Transformers 4.32.1
- Pytorch 2.0.1+cu117
- Datasets 2.14.4
- Tokenizers 0.13.3
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