metadata
language:
- en
license: apache-2.0
base_model: pszemraj/tFINE-base-300m
tags:
- generated_from_trainer
datasets:
- samsum
metrics:
- rouge
model-index:
- name: tFINE-base-300m-samsum
results:
- task:
name: Summarization
type: summarization
dataset:
name: samsum
type: samsum
config: samsum
split: None
args: samsum
metrics:
- name: Rouge1
type: rouge
value: 42.3629
library_name: transformers
pipeline_tag: summarization
tFINE-base-300m-samsum
An example fine-tune of pszemraj/tFINE-base-300m for summarization using the samsum dataset. It achieves the following results on the evaluation set:
- Loss: 1.9820
- Rouge1: 42.3629
- Rouge2: 18.4285
- Rougel: 34.6339
- Rougelsum: 38.7792
- Gen Len: 27.8033
The base model was pre-trained with CTX 1024 and fine-tuned on samsum with 1024 CTX inputs.
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0001
- train_batch_size: 8
- eval_batch_size: 16
- seed: 17868
- gradient_accumulation_steps: 16
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 4.0
Training results
keep epoch 3 checkpt as final
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| 1.9528 | 0.9989 | 115 | 1.9189 | 40.093 | 18.2018 | 33.9749 | 36.9071 | 29.3333 |
| 1.5346 | 1.9978 | 230 | 1.8827 | 41.4676 | 18.3467 | 34.1909 | 38.2131 | 27.6633 |
| 1.1696 | 2.9967 | 345 | 1.9820 | 42.3629 | 18.4285 | 34.6339 | 38.7792 | 27.8033 |
| 0.9359 | 3.9957 | 460 | 2.1588 | 41.2237 | 17.8161 | 33.7101 | 37.9569 | 30.18 |