metadata

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-v2
    results: []

spa-eng-pos-tagging-v2

This model is a fine-tuned version of distilbert-base-multilingual-cased on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.4432
Accuracy: 0.8418
Precision: 0.8395
Recall: 0.7600
F1: 0.7676
Hamming Loss: 0.1582

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: 1e-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
1.4285	1.0	1744	1.2584	0.5671	0.6506	0.4372	0.4716	0.4329
1.1788	2.0	3488	1.0023	0.6388	0.6753	0.5323	0.5578	0.3612
0.9144	3.0	5232	0.7885	0.7093	0.7259	0.6091	0.6281	0.2907
0.78	4.0	6976	0.6970	0.7439	0.7517	0.6527	0.6673	0.2561
0.6565	5.0	8720	0.6072	0.7765	0.7792	0.6838	0.6952	0.2235
0.5845	6.0	10464	0.5438	0.7995	0.7974	0.7125	0.7221	0.2005
0.5158	7.0	12208	0.5127	0.8132	0.8180	0.7250	0.7362	0.1868
0.4697	8.0	13952	0.4939	0.8186	0.8188	0.7345	0.7438	0.1814
0.4251	9.0	15696	0.4712	0.8334	0.8349	0.7502	0.7591	0.1666
0.4039	10.0	17440	0.4564	0.8381	0.8382	0.7538	0.7629	0.1619
0.3826	11.0	19184	0.4479	0.8397	0.8399	0.7565	0.7656	0.1603
0.3691	12.0	20928	0.4432	0.8418	0.8395	0.7600	0.7676	0.1582

Framework versions

Transformers 4.32.0
Pytorch 2.0.1+cu118
Tokenizers 0.13.3