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---
base_model: google/umt5-base
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: umt5-base-quechua-espanol-finetuned-model-v3
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. -->
# umt5-base-quechua-espanol-finetuned-model-v3
This model is a fine-tuned version of [google/umt5-base](https://huggingface.co/google/umt5-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4864
## 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: 0.0002
- train_batch_size: 22
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- num_epochs: 2
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 3.0774 | 0.2251 | 1000 | 2.5173 |
| 2.5309 | 0.4502 | 2000 | 2.1156 |
| 2.2481 | 0.6754 | 3000 | 1.8950 |
| 2.065 | 0.9005 | 4000 | 1.7553 |
| 1.8966 | 1.1256 | 5000 | 1.6603 |
| 1.8182 | 1.3507 | 6000 | 1.5891 |
| 1.762 | 1.5759 | 7000 | 1.5303 |
| 1.7083 | 1.8010 | 8000 | 1.4864 |
### Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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