---
license: apache-2.0
base_model: t5-base
tags:
- generated_from_trainer
metrics:
- bleu
- wer
model-index:
- name: randomization_model_new
  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. -->

# randomization_model_new

This model is a fine-tuned version of [t5-base](https://huggingface.co/t5-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.5870
- Bleu: 0.0001
- Wer: 0.9532
- Rougel: 0.1256
- Gen Len: 19.0

## 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: 2e-05
- train_batch_size: 10
- eval_batch_size: 10
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Bleu   | Wer    | Rougel | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:-------:|
| 2.5389        | 0.1   | 100  | 2.1621          | 0.0    | 0.9613 | 0.1062 | 18.9925 |
| 2.509         | 0.2   | 200  | 2.0311          | 0.0    | 0.9589 | 0.1112 | 19.0    |
| 2.4189        | 0.3   | 300  | 1.9480          | 0.0    | 0.9577 | 0.1143 | 18.9995 |
| 2.3174        | 0.4   | 400  | 1.8855          | 0.0001 | 0.9569 | 0.1163 | 19.0    |
| 2.2219        | 0.5   | 500  | 1.8416          | 0.0001 | 0.956  | 0.118  | 19.0    |
| 2.1971        | 0.6   | 600  | 1.8083          | 0.0001 | 0.9556 | 0.1193 | 19.0    |
| 2.1342        | 0.7   | 700  | 1.7758          | 0.0001 | 0.9551 | 0.1207 | 19.0    |
| 2.179         | 0.8   | 800  | 1.7494          | 0.0001 | 0.955  | 0.121  | 19.0    |
| 2.0986        | 0.9   | 900  | 1.7289          | 0.0001 | 0.9546 | 0.1219 | 19.0    |
| 2.0907        | 1.0   | 1000 | 1.7141          | 0.0001 | 0.9542 | 0.1225 | 19.0    |
| 2.0455        | 1.1   | 1100 | 1.6966          | 0.0001 | 0.9542 | 0.1229 | 19.0    |
| 2.033         | 1.2   | 1200 | 1.6802          | 0.0001 | 0.954  | 0.1234 | 19.0    |
| 2.0234        | 1.3   | 1300 | 1.6669          | 0.0001 | 0.9538 | 0.1234 | 19.0    |
| 2.0025        | 1.4   | 1400 | 1.6557          | 0.0001 | 0.954  | 0.1236 | 19.0    |
| 2.0098        | 1.5   | 1500 | 1.6467          | 0.0001 | 0.9539 | 0.1236 | 19.0    |
| 1.9495        | 1.6   | 1600 | 1.6381          | 0.0001 | 0.9539 | 0.1242 | 19.0    |
| 1.964         | 1.7   | 1700 | 1.6310          | 0.0001 | 0.9537 | 0.1244 | 19.0    |
| 1.9228        | 1.8   | 1800 | 1.6233          | 0.0001 | 0.9537 | 0.1245 | 19.0    |
| 1.9449        | 1.9   | 1900 | 1.6184          | 0.0001 | 0.9535 | 0.1248 | 19.0    |
| 1.9273        | 2.0   | 2000 | 1.6118          | 0.0001 | 0.9536 | 0.1245 | 19.0    |
| 1.9191        | 2.1   | 2100 | 1.6066          | 0.0001 | 0.9535 | 0.1248 | 19.0    |
| 1.9337        | 2.2   | 2200 | 1.6031          | 0.0001 | 0.9534 | 0.1251 | 19.0    |
| 1.9273        | 2.3   | 2300 | 1.5989          | 0.0001 | 0.9535 | 0.1253 | 19.0    |
| 1.9076        | 2.4   | 2400 | 1.5945          | 0.0001 | 0.9535 | 0.1251 | 19.0    |
| 1.8714        | 2.5   | 2500 | 1.5939          | 0.0001 | 0.9534 | 0.1253 | 19.0    |
| 1.9247        | 2.6   | 2600 | 1.5915          | 0.0001 | 0.9533 | 0.1253 | 19.0    |
| 1.8908        | 2.7   | 2700 | 1.5884          | 0.0001 | 0.9532 | 0.1256 | 19.0    |
| 1.8858        | 2.8   | 2800 | 1.5875          | 0.0001 | 0.9532 | 0.1254 | 19.0    |
| 1.9158        | 2.9   | 2900 | 1.5872          | 0.0001 | 0.9532 | 0.1256 | 19.0    |
| 1.8725        | 3.0   | 3000 | 1.5870          | 0.0001 | 0.9532 | 0.1256 | 19.0    |


### Framework versions

- Transformers 4.41.0
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1