fine_tune_sentiment_analysis_fin

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

• Loss: 0.4803
• Mse: 0.3574
• Mae: 0.5231
• R2: -0.0000

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: 64
• eval_batch_size: 64
• seed: 42
• optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: linear
• num_epochs: 30

Training results

Training Loss	Epoch	Step	Validation Loss	Mse	Mae	R2
No log	1.0	19	0.3604	0.3574	0.5231	-0.0000
No log	2.0	38	0.3654	0.3574	0.5231	-0.0000
No log	3.0	57	0.3713	0.3574	0.5231	-0.0000
No log	4.0	76	0.3799	0.3574	0.5231	-0.0000
No log	5.0	95	0.3796	0.3574	0.5231	-0.0000
No log	6.0	114	0.3925	0.3574	0.5231	-0.0000
No log	7.0	133	0.3793	0.3574	0.5231	-0.0000
No log	8.0	152	0.3993	0.3574	0.5231	-0.0000
No log	9.0	171	0.3957	0.3574	0.5231	-0.0000
No log	10.0	190	0.4051	0.3574	0.5231	-0.0000
No log	11.0	209	0.4216	0.3574	0.5231	-0.0000
No log	12.0	228	0.4195	0.3574	0.5231	-0.0000
No log	13.0	247	0.4499	0.3574	0.5231	-0.0000
No log	14.0	266	0.4140	0.3574	0.5231	-0.0000
No log	15.0	285	0.4346	0.3574	0.5231	-0.0000
No log	16.0	304	0.4319	0.3574	0.5231	-0.0000
No log	17.0	323	0.4504	0.3574	0.5231	-0.0000
No log	18.0	342	0.4391	0.3574	0.5231	-0.0000
No log	19.0	361	0.4549	0.3574	0.5231	-0.0000
No log	20.0	380	0.4656	0.3574	0.5231	-0.0000
No log	21.0	399	0.4536	0.3574	0.5231	-0.0000
No log	22.0	418	0.4621	0.3574	0.5231	-0.0000
No log	23.0	437	0.4709	0.3574	0.5231	-0.0000
No log	24.0	456	0.4806	0.3574	0.5231	-0.0000
No log	25.0	475	0.4725	0.3574	0.5231	-0.0000
No log	26.0	494	0.4713	0.3574	0.5231	-0.0000
0.2837	27.0	513	0.4697	0.3574	0.5231	-0.0000
0.2837	28.0	532	0.4768	0.3574	0.5231	-0.0000
0.2837	29.0	551	0.4795	0.3574	0.5231	-0.0000
0.2837	30.0	570	0.4803	0.3574	0.5231	-0.0000

Framework versions

• Transformers 4.47.1
• Pytorch 2.5.1+cu121
• Tokenizers 0.21.0