metadata

license: apache-2.0
tags:
  - generated_from_trainer
metrics:
  - rouge
model-index:
  - name: t5-base-DreamBank-Generation-Act-Char
    results: []
language:
  - en

t5-base-DreamBank-Generation-Act-Char

This model is a fine-tuned version of DReAMy-lib/t5-base-DreamBank-Generation-NER-Char on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.3058
Rouge1: 0.4708
Rouge2: 0.4040
Rougel: 0.4576
Rougelsum: 0.4572

Model description

Training procedure

The model is trained end-to-end using a text2text solution to annotate dream reports following the Activity feature from the Hall and Van de Castle scoring framework. Given a report, the model generates texts of the form [(initialiser : activity type : receiver)]. For those cases where initialiser and receiver are the same entity, the output will follow the [(initialiser : alone : none)] setting.

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

learning_rate: 0.001
train_batch_size: 16
eval_batch_size: 16
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 10
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum
No log	1.0	49	0.3674	0.4008	0.3122	0.3821	0.3812
No log	2.0	98	0.3200	0.4240	0.3433	0.4130	0.4121
No log	3.0	147	0.2845	0.4591	0.3883	0.4459	0.4455
No log	4.0	196	0.2508	0.4614	0.3930	0.4504	0.4497
No log	5.0	245	0.2632	0.4614	0.3929	0.4467	0.4459
No log	6.0	294	0.2688	0.4706	0.4036	0.4537	0.4534
No log	7.0	343	0.2790	0.4682	0.4043	0.4559	0.4556
No log	8.0	392	0.2895	0.4670	0.3972	0.4529	0.4534
No log	9.0	441	0.3058	0.4708	0.4040	0.4576	0.4572
No log	10.0	490	0.3169	0.4690	0.4001	0.4547	0.4544

Framework versions

Transformers 4.25.1
Pytorch 1.12.1
Datasets 2.5.1
Tokenizers 0.12.1