metadata

base_model: xxxxxxxxx
tags:
  - generated_from_trainer
datasets:
  - AmazonScience/massive
metrics:
  - f1
model-index:
  - name: massive_indo
    results: []

massive_indo

This model is a fine-tuned version of xxxxxxxxx on the massive dataset. It achieves the following results on the evaluation set:

Loss: 0.6572
F1: 0.9265

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
num_epochs: 20

Training results

Training Loss	Epoch	Step	Validation Loss	F1
4.6759	0.7	100	4.5686	0.0756
4.1696	1.41	200	4.1337	0.1459
3.7162	2.11	300	3.7519	0.2513
3.3933	2.82	400	3.4123	0.3291
3.0368	3.52	500	3.0874	0.4287
2.7163	4.23	600	2.7851	0.5446
2.4295	4.93	700	2.5342	0.5967
2.192	5.63	800	2.2814	0.6738
1.9818	6.34	900	2.0643	0.7221
1.7487	7.04	1000	1.8860	0.7589
1.6227	7.75	1100	1.7132	0.8021
1.4186	8.45	1200	1.5550	0.8249
1.2316	9.15	1300	1.4266	0.8378
1.1508	9.86	1400	1.3024	0.8547
1.0137	10.56	1500	1.1962	0.8708
0.9242	11.27	1600	1.1050	0.8807
0.877	11.97	1700	1.0273	0.8908
0.7244	12.68	1800	0.9580	0.8946
0.7141	13.38	1900	0.8928	0.9016
0.6071	14.08	2000	0.8448	0.9128
0.6166	14.79	2100	0.7980	0.9112
0.6017	15.49	2200	0.7613	0.9175
0.5192	16.2	2300	0.7300	0.9204
0.4669	16.9	2400	0.7112	0.9172
0.4539	17.61	2500	0.6872	0.9247
0.438	18.31	2600	0.6698	0.9248
0.4435	19.01	2700	0.6612	0.9256
0.4141	19.72	2800	0.6572	0.9265

Framework versions

Transformers 4.33.3
Pytorch 2.0.1+cu118
Tokenizers 0.13.3