---
tags:
- generated_from_trainer
metrics:
- wer
- bleu
base_model: Samuael/amBART_1000
model-index:
- name: amBART_261
  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. -->

# amBART_261

This model is a fine-tuned version of [Samuael/amBART_1000](https://huggingface.co/Samuael/amBART_1000) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.9604
- Wer: 2.7857
- Cer: 3.6889
- Bleu: 0.0
- Lr: 0.02

## 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: 0.02
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     | Cer    | Bleu   | Lr   |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:------:|:----:|
| No log        | 1.0   | 1    | 3.9328          | 1.0     | 4.6333 | 0.0    | 0.02 |
| No log        | 2.0   | 2    | 4.1008          | 1.0     | 6.1778 | 0.0    | 0.02 |
| No log        | 3.0   | 3    | 3.8971          | 1.0714  | 3.7556 | 0.0    | 0.02 |
| No log        | 4.0   | 4    | 3.5169          | 1.5714  | 6.2889 | 0.0    | 0.02 |
| No log        | 5.0   | 5    | 3.4597          | 10.0714 | 6.1889 | 0.0    | 0.02 |
| No log        | 6.0   | 6    | 3.4714          | 1.0     | 6.3222 | 0.0    | 0.02 |
| No log        | 7.0   | 7    | 3.1601          | 1.0     | 6.0667 | 0.0    | 0.02 |
| No log        | 8.0   | 8    | 2.5631          | 1.0     | 0.7667 | 0.0    | 0.02 |
| No log        | 9.0   | 9    | 2.6357          | 2.0     | 6.3667 | 0.0    | 0.02 |
| No log        | 10.0  | 10   | 3.1707          | 2.3571  | 6.5111 | 0.0    | 0.02 |
| No log        | 11.0  | 11   | 2.9462          | 1.1429  | 0.7    | 0.0    | 0.02 |
| No log        | 12.0  | 12   | 3.0437          | 1.0     | 6.2111 | 0.0    | 0.02 |
| No log        | 13.0  | 13   | 2.6371          | 19.2143 | 8.8667 | 0.0    | 0.02 |
| No log        | 14.0  | 14   | 2.4126          | 7.7143  | 7.1    | 0.0    | 0.02 |
| No log        | 15.0  | 15   | 2.6156          | 19.1429 | 6.1    | 0.0    | 0.02 |
| No log        | 16.0  | 16   | 2.7927          | 19.5714 | 6.1778 | 0.0    | 0.02 |
| No log        | 17.0  | 17   | 2.6685          | 1.0     | 3.3333 | 0.0    | 0.02 |
| No log        | 18.0  | 18   | 2.9460          | 1.0     | 0.8111 | 0.0    | 0.02 |
| No log        | 19.0  | 19   | 3.3183          | 1.0714  | 3.4556 | 0.0    | 0.02 |
| No log        | 20.0  | 20   | 3.7492          | 1.2143  | 3.5222 | 0.0    | 0.02 |
| No log        | 21.0  | 21   | 3.8371          | 9.1429  | 6.6111 | 0.0    | 0.02 |
| No log        | 22.0  | 22   | 3.7951          | 13.9286 | 6.3333 | 0.0    | 0.02 |
| No log        | 23.0  | 23   | 3.4253          | 12.0714 | 6.1556 | 0.0    | 0.02 |
| No log        | 24.0  | 24   | 3.4148          | 1.0714  | 0.7333 | 0.0    | 0.02 |
| No log        | 25.0  | 25   | 3.0110          | 8.7143  | 5.9889 | 0.2910 | 0.02 |
| No log        | 26.0  | 26   | 2.7432          | 1.0     | 1.1444 | 0.0    | 0.02 |
| No log        | 27.0  | 27   | 2.5661          | 1.4286  | 0.9333 | 0.0    | 0.02 |
| No log        | 28.0  | 28   | 2.6703          | 1.0     | 3.4889 | 0.0    | 0.02 |
| No log        | 29.0  | 29   | 2.9169          | 18.7143 | 6.1111 | 0.0    | 0.02 |
| No log        | 30.0  | 30   | 3.1300          | 4.0     | 4.3667 | 0.0    | 0.02 |
| No log        | 31.0  | 31   | 3.2927          | 6.0     | 5.6222 | 0.0    | 0.02 |
| No log        | 32.0  | 32   | 3.0442          | 6.5714  | 6.0444 | 0.0    | 0.02 |
| No log        | 33.0  | 33   | 2.7768          | 1.7143  | 3.5222 | 0.0    | 0.02 |
| No log        | 34.0  | 34   | 2.6387          | 1.2857  | 3.4778 | 0.0    | 0.02 |
| No log        | 35.0  | 35   | 2.4790          | 1.2143  | 3.4444 | 0.0    | 0.02 |
| No log        | 36.0  | 36   | 2.3595          | 5.9286  | 4.8111 | 0.0    | 0.02 |
| No log        | 37.0  | 37   | 2.2934          | 7.6429  | 5.3    | 0.0    | 0.02 |
| No log        | 38.0  | 38   | 2.2778          | 1.6429  | 3.7556 | 1.6467 | 0.02 |
| No log        | 39.0  | 39   | 2.2839          | 6.0714  | 4.7333 | 0.0    | 0.02 |
| No log        | 40.0  | 40   | 2.2559          | 1.2857  | 0.8111 | 0.0    | 0.02 |
| No log        | 41.0  | 41   | 2.2032          | 2.5714  | 4.2333 | 0.0    | 0.02 |
| No log        | 42.0  | 42   | 2.1507          | 1.1429  | 3.4444 | 0.0    | 0.02 |
| No log        | 43.0  | 43   | 2.1281          | 1.0     | 0.7556 | 0.0    | 0.02 |
| No log        | 44.0  | 44   | 2.1175          | 1.5714  | 3.4556 | 0.0    | 0.02 |
| No log        | 45.0  | 45   | 2.0781          | 4.5714  | 4.3444 | 0.5569 | 0.02 |
| No log        | 46.0  | 46   | 2.0383          | 1.4286  | 3.3889 | 1.8161 | 0.02 |
| No log        | 47.0  | 47   | 2.0069          | 1.4286  | 3.3889 | 1.8161 | 0.02 |
| No log        | 48.0  | 48   | 1.9878          | 1.3571  | 3.3667 | 0.0    | 0.02 |
| No log        | 49.0  | 49   | 1.9714          | 3.6429  | 3.9556 | 0.0    | 0.02 |
| No log        | 50.0  | 50   | 1.9604          | 2.7857  | 3.6889 | 0.0    | 0.02 |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2