File size: 1,754 Bytes
5fd06b5 7b7525e 5fd06b5 d3ae372 01d463c d3ae372 d564c9a d3ae372 01d463c c3edcaa 5fd06b5 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 |
---
tags:
- generated_from_trainer
datasets:
- navjordj/SNL_summarization
model-index:
- name: t5-large-snl-2
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: snl-summarization
type: snl-summarization
metrics:
- name: Rouge1
type: rouge
value: 35.1506
inference:
parameters:
max_length: 160
repetition_penalty: 1.2
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# t5-large-snl-2
This model is a fine-tuned version of [navjordj/t5-large-snl](https://huggingface.co/navjordj/t5-large-snl) on the navjordj/SNL_summarization dataset.
It achieves the following results on the evaluation set:
- eval_loss: 1.8691
- eval_rouge1: 35.1506
- eval_rouge2: 16.0888
- eval_rougeL: 29.7007
- eval_rougeLsum: 32.4251
- eval_gen_len: 41.5629
- eval_runtime: 261.235
- eval_samples_per_second: 3.135
- eval_steps_per_second: 0.199
- step: 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: 16
- eval_batch_size: 16
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20.0
### Framework versions
- Transformers 4.27.0.dev0
- Pytorch 1.13.1
- Datasets 2.10.1
- Tokenizers 0.13.2
|