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vinh120203/
rwBl__sentiment_analysis-heBERT

Name: rwBl__sentiment_analysis-heBERT
Availability: InStock

generated_from_trainer

avichr/heBERT_sentiment_analysis

finetune

autotrain_compatible

endpoints_compatible

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heBERT_sentiment_analysis

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

Loss: 0.4046
Accuracy: 0.8563
F1: 0.8554
Precision: 0.8551
Recall: 0.8567

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: 32
eval_batch_size: 32
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 100
num_epochs: 3
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Precision	Recall
2.5497	0.0820	50	0.7625	0.7076	0.6676	0.7357	0.7090
0.6821	0.1639	100	0.5465	0.7898	0.7818	0.7916	0.7905
0.5475	0.2459	150	0.4972	0.8155	0.8074	0.8198	0.8161
0.5397	0.3279	200	0.4992	0.8213	0.8168	0.8210	0.8217
0.5328	0.4098	250	0.4999	0.8101	0.7988	0.8213	0.8109
0.5052	0.4918	300	0.4983	0.8108	0.8131	0.8191	0.8107
0.4627	0.5738	350	0.4597	0.8291	0.8290	0.8317	0.8291
0.4565	0.6557	400	0.4328	0.8362	0.8332	0.8356	0.8366
0.4187	0.7377	450	0.4416	0.8402	0.8361	0.8413	0.8406
0.4611	0.8197	500	0.4655	0.8308	0.8306	0.8304	0.8311
0.436	0.9016	550	0.4246	0.8335	0.8343	0.8350	0.8338
0.4118	0.9836	600	0.4179	0.8429	0.8418	0.8425	0.8431
0.4019	1.0656	650	0.4041	0.8436	0.8426	0.8426	0.8438
0.419	1.1475	700	0.4238	0.8418	0.8405	0.8403	0.8422
0.3656	1.2295	750	0.4046	0.8485	0.8486	0.8486	0.8487
0.3559	1.3115	800	0.4032	0.8414	0.8415	0.8414	0.8417
0.3529	1.3934	850	0.4229	0.8489	0.8452	0.8498	0.8494
0.3247	1.4754	900	0.4198	0.8491	0.8463	0.8491	0.8494
0.3435	1.5574	950	0.4254	0.8395	0.8413	0.8468	0.8394
0.3519	1.6393	1000	0.4414	0.8447	0.8427	0.8472	0.8448
0.3763	1.7213	1050	0.4097	0.8534	0.8521	0.8534	0.8536
0.3739	1.8033	1100	0.3926	0.8523	0.8487	0.8540	0.8527
0.3807	1.8852	1150	0.3896	0.8528	0.8515	0.8514	0.8531
0.3655	1.9672	1200	0.3897	0.8526	0.8504	0.8535	0.8528
0.3125	2.0492	1250	0.4199	0.8539	0.8540	0.8545	0.8540
0.2851	2.1311	1300	0.4107	0.8550	0.8541	0.8554	0.8551
0.2907	2.2131	1350	0.4093	0.8527	0.8532	0.8539	0.8528
0.2619	2.2951	1400	0.4085	0.8585	0.8572	0.8573	0.8588
0.2619	2.3770	1450	0.4166	0.8490	0.8501	0.8523	0.8491
0.2863	2.4590	1500	0.4046	0.8548	0.8538	0.8536	0.8550
0.2604	2.5410	1550	0.4143	0.8550	0.8544	0.8541	0.8552
0.2778	2.6230	1600	0.4021	0.8532	0.8540	0.8551	0.8533
0.2579	2.7049	1650	0.4071	0.8505	0.8518	0.8542	0.8505
0.2734	2.7869	1700	0.4069	0.8565	0.8566	0.8567	0.8567
0.2873	2.8689	1750	0.4006	0.8567	0.8563	0.8563	0.8569
0.2568	2.9508	1800	0.3998	0.8567	0.8568	0.8570	0.8569

Framework versions

Transformers 4.42.4
Pytorch 2.3.1+cu121
Tokenizers 0.19.1

vinh120203/rwBl__sentiment_analysis-heBERT

heBERT_sentiment_analysis

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

vinh120203/
rwBl__sentiment_analysis-heBERT