README.md

metadata

tags:
  - generated_from_trainer
metrics:
  - rouge
model-index:
  - name: ViT-RadBert_Mimic
    results: []

ViT-RadBert_Mimic

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

• Loss: 0.7877
• Rouge1: 0.0
• Rouge2: 0.0
• Rougel: 0.0
• Rougelsum: 0.0
• Gen Len: 20.0

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: 5e-05
• train_batch_size: 4
• eval_batch_size: 4
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 15

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum	Gen Len
0.2467	1.0	1750	0.2455	15.3883	0.0	15.4185	15.4293	12.065
0.2303	2.0	3500	0.2513	13.5368	0.0	13.5094	13.4921	14.028
0.233	3.0	5250	0.2487	0.0	0.0	0.0	0.0	20.0
0.2317	4.0	7000	0.2515	0.0	0.0	0.0	0.0	20.0
0.229	5.0	8750	0.2563	0.0	0.0	0.0	0.0	20.0
0.2334	6.0	10500	0.5032	0.0	0.0	0.0	0.0	20.0
0.216	7.0	12250	0.6445	0.0	0.0	0.0	0.0	20.0
0.2154	8.0	14000	0.7287	0.0	0.0	0.0	0.0	20.0
0.2065	9.0	15750	0.7666	0.0	0.0	0.0	0.0	20.0
0.206	10.0	17500	0.6641	0.0	0.0	0.0	0.0	20.0
0.2014	11.0	19250	0.7032	0.0	0.0	0.0	0.0	20.0
0.1784	12.0	21000	0.7845	0.0	0.0	0.0	0.0	20.0
0.1854	13.0	22750	0.8179	0.0	0.0	0.0	0.0	20.0
0.1801	14.0	24500	0.7788	0.0	0.0	0.0	0.0	20.0
0.1743	15.0	26250	0.7877	0.0	0.0	0.0	0.0	20.0

Framework versions

• Transformers 4.37.1
• Pytorch 1.13.1+cu117
• Datasets 2.15.0
• Tokenizers 0.15.1