---
base_model: nadsoft/Hamsa-large-v0.1-beta
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: hamsa-pretrained
  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. -->

# hamsa-pretrained

This model is a fine-tuned version of [nadsoft/Hamsa-large-v0.1-beta](https://huggingface.co/nadsoft/Hamsa-large-v0.1-beta) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4344
- Wer: 29.2057

## 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: 0.00025
- train_batch_size: 8
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 35000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer     |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|
| 1.895         | 0.01  | 1000  | 1.8765          | 86.7012 |
| 1.6569        | 0.01  | 2000  | 1.5809          | 84.0907 |
| 1.3312        | 0.02  | 3000  | 1.3458          | 75.7090 |
| 1.2369        | 0.02  | 4000  | 1.2389          | 73.1365 |
| 1.1518        | 0.03  | 5000  | 1.1097          | 66.8170 |
| 1.0135        | 0.03  | 6000  | 1.0616          | 65.1843 |
| 1.0965        | 0.04  | 7000  | 1.0084          | 65.8582 |
| 0.867         | 0.04  | 8000  | 0.9305          | 57.6093 |
| 0.9425        | 0.05  | 9000  | 0.8907          | 55.4854 |
| 0.9501        | 0.05  | 10000 | 0.8393          | 54.0212 |
| 0.8602        | 0.06  | 11000 | 0.8096          | 53.4968 |
| 0.7596        | 0.06  | 12000 | 0.7761          | 51.9305 |
| 0.7334        | 0.07  | 13000 | 0.7694          | 49.4411 |
| 0.708         | 0.07  | 14000 | 0.7336          | 47.0040 |
| 0.7112        | 0.08  | 15000 | 0.7149          | 47.5783 |
| 0.6989        | 0.08  | 16000 | 0.6713          | 44.2986 |
| 0.7025        | 0.09  | 17000 | 0.6639          | 43.7481 |
| 0.6127        | 0.09  | 18000 | 0.6477          | 42.9127 |
| 0.6342        | 0.1   | 19000 | 0.6298          | 42.6826 |
| 0.6174        | 0.1   | 20000 | 0.6080          | 40.1172 |
| 0.5551        | 0.11  | 21000 | 0.5896          | 39.0398 |
| 0.5353        | 0.11  | 22000 | 0.5753          | 39.1253 |
| 0.5528        | 0.12  | 23000 | 0.5588          | 40.2881 |
| 0.5423        | 0.12  | 24000 | 0.5445          | 35.6606 |
| 0.5069        | 0.13  | 25000 | 0.5304          | 35.9358 |
| 0.4356        | 0.13  | 26000 | 0.5187          | 34.4930 |
| 0.5111        | 0.14  | 27000 | 0.5035          | 33.4227 |
| 0.5613        | 0.14  | 28000 | 0.4912          | 33.0952 |
| 0.4165        | 0.15  | 29000 | 0.4825          | 32.0155 |
| 0.4736        | 0.15  | 30000 | 0.4716          | 32.0914 |
| 0.4213        | 0.16  | 31000 | 0.4618          | 31.6026 |
| 0.4242        | 0.16  | 32000 | 0.4514          | 30.3757 |
| 0.3837        | 0.17  | 33000 | 0.4448          | 30.3116 |
| 0.4321        | 0.17  | 34000 | 0.4377          | 29.4691 |
| 0.4268        | 0.18  | 35000 | 0.4344          | 29.2057 |


### Framework versions

- Transformers 4.37.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.16.2.dev0
- Tokenizers 0.15.0