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Bainbridge/
umberto-uncased-covid-sentiment

Name: umberto-uncased-covid-sentiment
Availability: InStock

generated_from_trainer

Musixmatch/umberto-wikipedia-uncased-v1

finetune

autotrain_compatible

endpoints_compatible

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umberto-wikipedia-uncased-v1

This model is a fine-tuned version of Musixmatch/umberto-wikipedia-uncased-v1 on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.4643
F1: 0.6160

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: 128
eval_batch_size: 32
seed: 0
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: constant
lr_scheduler_warmup_ratio: 0.05
num_epochs: 5.0

Training results

Training Loss	Epoch	Step	Validation Loss	F1
0.5923	0.33	20	0.6075	0.2974
0.6694	0.67	40	0.5938	0.2974
0.5225	1.0	60	0.5346	0.3024
0.5458	1.33	80	0.5172	0.4682
0.5052	1.67	100	0.5550	0.4361
0.3689	2.0	120	0.5188	0.4395
0.4097	2.33	140	0.4918	0.4676
0.4904	2.67	160	0.4756	0.4640
0.3696	3.0	180	0.4788	0.4688
0.3631	3.33	200	0.4751	0.4735
0.4345	3.67	220	0.4609	0.4797
0.3398	4.0	240	0.4637	0.5673
0.2985	4.33	260	0.4850	0.5092
0.3248	4.67	280	0.5089	0.6057
0.3323	5.0	300	0.4643	0.6160

Framework versions

Transformers 4.34.0.dev0
Pytorch 2.1.0.dev20230628+cu121
Datasets 2.14.5
Tokenizers 0.14.0

Bainbridge/umberto-uncased-covid-sentiment

umberto-wikipedia-uncased-v1

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

Bainbridge/
umberto-uncased-covid-sentiment