---
license: apache-2.0
base_model: google/flan-t5-base
tags:
- generated_from_trainer
metrics:
- bleu
model-index:
- name: Nahuatl_Espanol_v1
  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. -->

# Nahuatl_Espanol_v1

This model is a fine-tuned version of [google/flan-t5-base](https://huggingface.co/google/flan-t5-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.3093
- Bleu: 0.928
- Gen Len: 17.3008

## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Bleu   | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|
| No log        | 0.1   | 100  | 3.4034          | 0.3143 | 17.3089 |
| No log        | 0.2   | 200  | 3.1638          | 0.3187 | 17.4173 |
| No log        | 0.3   | 300  | 3.0323          | 0.3292 | 17.2922 |
| No log        | 0.4   | 400  | 2.9391          | 0.3713 | 17.1362 |
| 3.4051        | 0.5   | 500  | 2.8715          | 0.4182 | 17.2461 |
| 3.4051        | 0.6   | 600  | 2.8084          | 0.4782 | 17.2052 |
| 3.4051        | 0.71  | 700  | 2.7614          | 0.4541 | 17.1109 |
| 3.4051        | 0.81  | 800  | 2.7171          | 0.6082 | 17.2327 |
| 3.4051        | 0.91  | 900  | 2.6860          | 0.7904 | 17.2443 |
| 2.961         | 1.01  | 1000 | 2.6516          | 0.8488 | 17.3227 |
| 2.961         | 1.11  | 1100 | 2.6256          | 0.8094 | 17.3409 |
| 2.961         | 1.21  | 1200 | 2.5967          | 0.7545 | 17.3147 |
| 2.961         | 1.31  | 1300 | 2.5753          | 0.7891 | 17.2418 |
| 2.961         | 1.41  | 1400 | 2.5545          | 0.7925 | 17.2849 |
| 2.7764        | 1.51  | 1500 | 2.5335          | 0.7728 | 17.3243 |
| 2.7764        | 1.61  | 1600 | 2.5163          | 0.8055 | 17.4302 |
| 2.7764        | 1.71  | 1700 | 2.4993          | 0.843  | 17.2501 |
| 2.7764        | 1.81  | 1800 | 2.4840          | 0.8297 | 17.2136 |
| 2.7764        | 1.92  | 1900 | 2.4719          | 0.8457 | 17.3364 |
| 2.6783        | 2.02  | 2000 | 2.4598          | 0.9152 | 17.2453 |
| 2.6783        | 2.12  | 2100 | 2.4458          | 0.8597 | 17.2405 |
| 2.6783        | 2.22  | 2200 | 2.4345          | 0.8741 | 17.2436 |
| 2.6783        | 2.32  | 2300 | 2.4245          | 0.8681 | 17.3492 |
| 2.6783        | 2.42  | 2400 | 2.4166          | 0.8936 | 17.2708 |
| 2.6228        | 2.52  | 2500 | 2.4055          | 0.9256 | 17.3568 |
| 2.6228        | 2.62  | 2600 | 2.3960          | 0.9354 | 17.3248 |
| 2.6228        | 2.72  | 2700 | 2.3873          | 0.9543 | 17.3961 |
| 2.6228        | 2.82  | 2800 | 2.3823          | 0.93   | 17.2564 |
| 2.6228        | 2.92  | 2900 | 2.3740          | 0.9701 | 17.2161 |
| 2.5527        | 3.02  | 3000 | 2.3671          | 0.9669 | 17.26   |
| 2.5527        | 3.12  | 3100 | 2.3583          | 0.8909 | 17.4082 |
| 2.5527        | 3.23  | 3200 | 2.3555          | 0.9186 | 17.3296 |
| 2.5527        | 3.33  | 3300 | 2.3508          | 0.9321 | 17.3119 |
| 2.5527        | 3.43  | 3400 | 2.3459          | 0.9821 | 17.2859 |
| 2.5106        | 3.53  | 3500 | 2.3410          | 0.9371 | 17.292  |
| 2.5106        | 3.63  | 3600 | 2.3373          | 0.9368 | 17.2756 |
| 2.5106        | 3.73  | 3700 | 2.3330          | 0.9312 | 17.295  |
| 2.5106        | 3.83  | 3800 | 2.3304          | 0.9827 | 17.2847 |
| 2.5106        | 3.93  | 3900 | 2.3263          | 0.9637 | 17.2867 |
| 2.5138        | 4.03  | 4000 | 2.3216          | 0.9209 | 17.3356 |
| 2.5138        | 4.13  | 4100 | 2.3198          | 0.9088 | 17.3548 |
| 2.5138        | 4.23  | 4200 | 2.3177          | 0.9193 | 17.3401 |
| 2.5138        | 4.33  | 4300 | 2.3151          | 0.937  | 17.3346 |
| 2.5138        | 4.44  | 4400 | 2.3142          | 0.9396 | 17.2953 |
| 2.4804        | 4.54  | 4500 | 2.3130          | 0.9446 | 17.3099 |
| 2.4804        | 4.64  | 4600 | 2.3109          | 0.9449 | 17.3018 |
| 2.4804        | 4.74  | 4700 | 2.3102          | 0.9363 | 17.3106 |
| 2.4804        | 4.84  | 4800 | 2.3095          | 0.9306 | 17.3033 |
| 2.4804        | 4.94  | 4900 | 2.3093          | 0.928  | 17.3008 |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2