metadata

base_model: allenai/scibert_scivocab_uncased
tags:
  - generated_from_trainer
metrics:
  - accuracy
  - precision
  - recall
  - f1
model-index:
  - name: test_AsymmetricLoss_25K_bs64_P4_N1
    results: []

test_AsymmetricLoss_25K_bs64_P4_N1

This model is a fine-tuned version of allenai/scibert_scivocab_uncased on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.6203
Accuracy: 0.7448
Precision: 0.0101
Recall: 0.2592
F1: 0.0194
Hamming: 0.2552

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: 40
eval_batch_size: 40
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
training_steps: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	F1	Hamming
0.6901	0.0	5	0.6457	0.6626	0.0099	0.3394	0.0192	0.3374
0.6344	0.0	10	0.6203	0.7448	0.0101	0.2592	0.0194	0.2552

Framework versions

Transformers 4.35.0.dev0
Pytorch 2.0.1+cu118
Datasets 2.7.1
Tokenizers 0.14.1