ericRosello/bert-base-uncased-finetuned-squad-frozen-v2

bert-base-uncased-finetuned-squad

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

• Loss: 1.4571

Model description

Most base model weights were frozen leaving only to finetune the last layer (qa outputs) and 3 last layers of the encoder.

Training and evaluation data

Achieved EM: 76.77388836329234, F1: 85.41893520501723

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 2e-05
• train_batch_size: 2
• eval_batch_size: 2
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss
1.2944	1.0	44262	1.3432
1.0152	2.0	88524	1.3450
1.0062	3.0	132786	1.4571

Framework versions

• Transformers 4.15.0
• Pytorch 1.10.0+cu111
• Datasets 1.17.0
• Tokenizers 0.10.3