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---
license: apache-2.0
base_model: distilbert-base-multilingual-cased
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: spa-eng-pos-tagging-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. -->
# spa-eng-pos-tagging-v3
This model is a fine-tuned version of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3384
- Accuracy: 0.9036
- Precision: 0.8993
- Recall: 0.8285
- F1: 0.8324
- Hamming Loss: 0.0964
## 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: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 12
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | Hamming Loss |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:---------:|:------:|:------:|:------------:|
| 0.7752 | 1.0 | 1744 | 0.7222 | 0.7342 | 0.7317 | 0.6509 | 0.6524 | 0.2658 |
| 0.6276 | 2.0 | 3488 | 0.5259 | 0.8059 | 0.8008 | 0.7205 | 0.7264 | 0.1941 |
| 0.4813 | 3.0 | 5232 | 0.4473 | 0.8353 | 0.8281 | 0.7604 | 0.7616 | 0.1647 |
| 0.4063 | 4.0 | 6976 | 0.4453 | 0.8393 | 0.8353 | 0.7616 | 0.7662 | 0.1607 |
| 0.3361 | 5.0 | 8720 | 0.3882 | 0.8658 | 0.8661 | 0.7894 | 0.7959 | 0.1342 |
| 0.2883 | 6.0 | 10464 | 0.3773 | 0.8747 | 0.8693 | 0.8022 | 0.8043 | 0.1253 |
| 0.2409 | 7.0 | 12208 | 0.3681 | 0.8803 | 0.8753 | 0.8056 | 0.8081 | 0.1197 |
| 0.2168 | 8.0 | 13952 | 0.3470 | 0.8899 | 0.8836 | 0.8161 | 0.8181 | 0.1101 |
| 0.1816 | 9.0 | 15696 | 0.3750 | 0.8838 | 0.8832 | 0.8071 | 0.8133 | 0.1162 |
| 0.1696 | 10.0 | 17440 | 0.3609 | 0.8914 | 0.8871 | 0.8161 | 0.8200 | 0.1086 |
| 0.1572 | 11.0 | 19184 | 0.3470 | 0.8977 | 0.8924 | 0.8228 | 0.8261 | 0.1023 |
| 0.1385 | 12.0 | 20928 | 0.3384 | 0.9036 | 0.8993 | 0.8285 | 0.8324 | 0.0964 |
### Framework versions
- Transformers 4.32.0
- Pytorch 2.0.1+cu118
- Tokenizers 0.13.3
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