edyfjm07/distilbert-base-uncased-finetuned-squad-es

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

• Train Loss: 0.4326
• Train End Logits Accuracy: 0.8250
• Train Start Logits Accuracy: 0.8238
• Validation Loss: 0.4552
• Validation End Logits Accuracy: 0.8284
• Validation Start Logits Accuracy: 0.7873
• Epoch: 9

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:

• optimizer: {'name': 'Adam', 'weight_decay': None, 'clipnorm': None, 'global_clipnorm': None, 'clipvalue': None, 'use_ema': False, 'ema_momentum': 0.99, 'ema_overwrite_frequency': None, 'jit_compile': True, 'is_legacy_optimizer': False, 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 500, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}
• training_precision: float32

Training results

Train Loss	Train End Logits Accuracy	Train Start Logits Accuracy	Validation Loss	Validation End Logits Accuracy	Validation Start Logits Accuracy	Epoch
3.9668	0.2262	0.1450	2.3827	0.4627	0.3470	0
1.8862	0.5138	0.4613	1.3513	0.5746	0.6269	1
1.1987	0.6388	0.6313	0.9111	0.6716	0.6866	2
0.8452	0.7275	0.7212	0.7251	0.7052	0.7164	3
0.6875	0.7400	0.7713	0.5832	0.7649	0.7724	4
0.5933	0.7825	0.7825	0.5321	0.7761	0.7799	5
0.5259	0.7962	0.8025	0.4906	0.7948	0.7687	6
0.4668	0.8288	0.8138	0.4699	0.8209	0.7799	7
0.4552	0.8450	0.8163	0.4554	0.8172	0.7724	8
0.4326	0.8250	0.8238	0.4552	0.8284	0.7873	9

Framework versions

• Transformers 4.40.1
• TensorFlow 2.15.0
• Datasets 2.19.1
• Tokenizers 0.19.1