liberta-large-topic_classification

This model is a fine-tuned version of Goader/liberta-large on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 0.7957
• Precision: 0.9167
• Recall: 0.8749
• F1: 0.8889
• Accuracy: 0.8971

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: 5e-05
• train_batch_size: 8
• eval_batch_size: 8
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
No log	1.0	88	0.7214	0.8294	0.7438	0.7532	0.7843
No log	2.0	176	0.6388	0.8181	0.7797	0.7826	0.8088
No log	3.0	264	0.8149	0.8625	0.8692	0.8617	0.8725
No log	4.0	352	0.8210	0.9171	0.8603	0.8695	0.8824
No log	5.0	440	0.7850	0.9173	0.8700	0.8841	0.8922
0.3285	6.0	528	0.7936	0.8987	0.8670	0.8770	0.8824
0.3285	7.0	616	0.7794	0.9217	0.8749	0.8913	0.8971
0.3285	8.0	704	0.7835	0.9217	0.8749	0.8913	0.8971
0.3285	9.0	792	0.7947	0.9167	0.8749	0.8889	0.8971
0.3285	10.0	880	0.7957	0.9167	0.8749	0.8889	0.8971

Framework versions

• Transformers 4.39.3
• Pytorch 1.11.0a0+17540c5
• Datasets 2.21.0
• Tokenizers 0.15.2