---
base_model: lnxdx/20_2000_1e-5_hp-mehrdad
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: B4_1000_1e-5_hp-myself-2
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# B4_1000_1e-5_hp-myself-2

This model is a fine-tuned version of [lnxdx/20_2000_1e-5_hp-mehrdad](https://huggingface.co/lnxdx/20_2000_1e-5_hp-mehrdad) on the None dataset.
It achieves the following results on the evaluation set:
- Loss on ShEMO train set: 0.7516
- Loss on ShEMO dev set:   0.6705
- WER on ShEMO train set:          28.02
- WER on ShEMO dev set:            31.16
- WER on Common Voice 13 test set: 19.34

## 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: 1e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- 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: 500
- training_steps: 1000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.8083        | 0.62  | 100  | 0.6766          | 0.3271 |
| 0.8414        | 1.25  | 200  | 0.6774          | 0.3259 |
| 0.8465        | 1.88  | 300  | 0.6686          | 0.3262 |
| 0.7819        | 2.5   | 400  | 0.6749          | 0.3207 |
| 0.7905        | 3.12  | 500  | 0.6848          | 0.3178 |
| 0.8078        | 3.75  | 600  | 0.6571          | 0.3245 |
| 0.7771        | 4.38  | 700  | 0.6683          | 0.3145 |
| 0.7786        | 5.0   | 800  | 0.6688          | 0.3137 |
| 0.7656        | 5.62  | 900  | 0.6703          | 0.3134 |
| 0.7516        | 6.25  | 1000 | 0.6706          | 0.3131 |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0