fineTuningXLMRoberta-TokenClassification-Spacy

This model is a fine-tuned version of cardiffnlp/twitter-xlm-roberta-base-sentiment on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.8479
• Precision: 0.2076
• Recall: 0.2102
• F1: 0.2089
• Accuracy: 0.6718

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: 32
• eval_batch_size: 32
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 15

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
No log	1.0	31	0.7433	0.2164	0.1421	0.1716	0.6557
No log	2.0	62	0.7177	0.2275	0.1848	0.2039	0.6727
No log	3.0	93	0.7054	0.1719	0.1949	0.1827	0.6637
No log	4.0	124	0.7148	0.1823	0.1919	0.1869	0.6628
No log	5.0	155	0.7018	0.2063	0.2061	0.2062	0.6853
No log	6.0	186	0.7310	0.1866	0.1919	0.1892	0.6711
No log	7.0	217	0.7272	0.2150	0.2071	0.2110	0.6897
No log	8.0	248	0.7878	0.1758	0.1848	0.1802	0.6582
No log	9.0	279	0.7727	0.2080	0.2071	0.2075	0.6814
No log	10.0	310	0.8099	0.1969	0.1959	0.1964	0.6688
No log	11.0	341	0.8119	0.2062	0.2030	0.2046	0.6766
No log	12.0	372	0.8227	0.2105	0.2112	0.2108	0.6770
No log	13.0	403	0.8300	0.2008	0.2051	0.2029	0.6744
No log	14.0	434	0.8409	0.2064	0.2081	0.2073	0.6739
No log	15.0	465	0.8479	0.2076	0.2102	0.2089	0.6718

Framework versions

• Transformers 4.44.0
• Pytorch 2.4.0
• Datasets 2.21.0
• Tokenizers 0.19.1