070524_epoch_2 – AI Model by adriansanz | AlphaNeural AI

You can deploy this model and start earning money today!

adriansanz/
070524_epoch_2

like

0

text-classification

generated_from_trainer

projecte-aina/roberta-base-ca-v2-cased-te

autotrain_compatible

endpoints_compatible

Views

No views yet

060524_epoch_2

This model is a fine-tuned version of projecte-aina/roberta-base-ca-v2-cased-te on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.6952
Accuracy: 0.7437
Precision: 0.7569
Recall: 0.7437
F1: 0.7404
Ratio: 0.6134

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: 10
eval_batch_size: 2
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 20
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.06
lr_scheduler_warmup_steps: 4
num_epochs: 1
label_smoothing_factor: 0.1

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	F1	Ratio
0.7924	0.1626	10	0.7754	0.7101	0.7233	0.7101	0.7057	0.3782
0.641	0.3252	20	0.8257	0.7227	0.7451	0.7227	0.7162	0.6513
0.8108	0.4878	30	0.7629	0.7563	0.7564	0.7563	0.7563	0.4916
0.736	0.6504	40	0.7167	0.7731	0.7751	0.7731	0.7727	0.4580
0.6973	0.8130	50	0.7419	0.7143	0.7448	0.7143	0.7051	0.6765
0.7981	0.9756	60	0.6962	0.7437	0.7569	0.7437	0.7404	0.6134

Framework versions

Transformers 4.40.1
Pytorch 2.2.1+cu121
Datasets 2.19.1
Tokenizers 0.19.1