metadata

base_model: allenai/scibert_scivocab_uncased
tags:
  - generated_from_trainer
metrics:
  - accuracy
  - precision
  - recall
  - f1
model-index:
  - name: test_TwoWayLoss_25K_bs64_P4_N1
    results: []

test_TwoWayLoss_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: 0.6265
Accuracy: 0.7094
Precision: 0.0099
Recall: 0.2915
F1: 0.0192
Hamming: 0.2906

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: 8
eval_batch_size: 8
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
0.6921	0.0	5	0.6507	0.6448	0.0101	0.3639	0.0196	0.3552
0.6402	0.0	10	0.6265	0.7094	0.0099	0.2915	0.0192	0.2906

Framework versions

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