RoBERTa-large-PM-M3-Voc-hf-finetuned-ner

This model was trained from scratch on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 0.3493
• Precision: 0.6836
• Recall: 0.8494
• F1: 0.7575
• Accuracy: 0.9116

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: 16
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: cosine
• num_epochs: 20

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
No log	1.0	23	1.2145	0.1762	0.0340	0.0569	0.7236
No log	2.0	46	0.8308	0.4435	0.3547	0.3942	0.7735
No log	3.0	69	0.7051	0.4419	0.6091	0.5122	0.7842
No log	4.0	92	0.6051	0.4989	0.6416	0.5613	0.8085
No log	5.0	115	0.5500	0.5501	0.6449	0.5937	0.8243
No log	6.0	138	0.5272	0.5351	0.6892	0.6025	0.8277
No log	7.0	161	0.5256	0.5426	0.7143	0.6167	0.8316
No log	8.0	184	0.4943	0.5583	0.7582	0.6431	0.8479
No log	9.0	207	0.4196	0.6217	0.7475	0.6788	0.8773
No log	10.0	230	0.4065	0.6270	0.7789	0.6948	0.8850
No log	11.0	253	0.4367	0.6012	0.8062	0.6887	0.8776
No log	12.0	276	0.3917	0.6301	0.8125	0.7098	0.8915
No log	13.0	299	0.3563	0.6736	0.8191	0.7393	0.9042
No log	14.0	322	0.3654	0.6653	0.8335	0.7400	0.9040
No log	15.0	345	0.3637	0.6611	0.8439	0.7414	0.9057
No log	16.0	368	0.3522	0.6785	0.8453	0.7528	0.9100
No log	17.0	391	0.3469	0.6841	0.8472	0.7569	0.9115
No log	18.0	414	0.3520	0.6821	0.8490	0.7565	0.9110
No log	19.0	437	0.3485	0.6848	0.8494	0.7583	0.9121
No log	20.0	460	0.3493	0.6836	0.8494	0.7575	0.9116

Framework versions

• Transformers 4.33.1
• Pytorch 2.0.1+cu118
• Datasets 2.14.5
• Tokenizers 0.13.3