---
tags:
- generated_from_trainer
- summarization
- book summary
metrics:
- rouge
dataset:
- kmfoda/booksum
model-index:
- name: long-t5-tglobal-large-booksum-WIP
  results:
  - task:
      type: summarization
      name: Summarization
    dataset:
      name: kmfoda/booksum
      type: kmfoda/booksum
      config: kmfoda--booksum
      split: test
    metrics:
    - type: rouge
      value: 25.6136
      name: ROUGE-1
      verified: true
      verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiY2E3ZWI5NjRiZGE3YTQ2YTg5MGNmNzI5NTdjN2U3OTNiNzhmMjBhMDVkZjcwZjg0MTEyMTM3MzQyZmI1NzNjYSIsInZlcnNpb24iOjF9.REYAFwePFucxAn1Twsh9BSov9KPsCML9nTjL9oIIWa3Hp8DwJ_syPmfNsYxGe2vvNVq5rzBKF9gsJW80pbo-Aw
    - type: rouge
      value: 2.8652
      name: ROUGE-2
      verified: true
      verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiMzk5Mjg0ZmRjYzg1NjM4MGMwOWYyOTM0ZDU2OTM2ZGJlYmM0OTVjNTI2NzcyMzU0MGI0M2I0ZmE0ZmY2NmRlNSIsInZlcnNpb24iOjF9.MzKSIqRjIV6V5YMYlvbRt2ca_CR5WFZ8DqOrUvDbiSyh7qbdU6F2LdDjB6eL-wzIR_DMF10sTtoF7H7wXs2GDw
    - type: rouge
      value: 12.4913
      name: ROUGE-L
      verified: true
      verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiZDMzMDZhYzg2N2Q0YTZiYWUzOGI2MTRjMmRlNGIzY2I0ZDU3YzQ1MWVkZDlkOTQzNDlhNjk1MWM2OWUwNDczYSIsInZlcnNpb24iOjF9.TysgYlvfe-4GJWDSFg8KQ97Bsu-kDX3VDamS6bi9q_60V3mBzIOz0M0slySuHXu5S4MJ8a0OCPWvskP0T4ZmCQ
    - type: rouge
      value: 23.1102
      name: ROUGE-LSUM
      verified: true
      verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiMzY3NmI2MDJkZTQ2MzMwMDg2NWZmM2Q5NjNmZTRkMTJiODViODZmODYyNTgwMzBkYzBmZDRmMWNjYjg5NjBkYSIsInZlcnNpb24iOjF9.XNvINLow-1mfiDbm_YcAM_l4c-gEV_V5oLKzBWh7Hdmi9gHP_Z86fqQn9Kj2nhOPFWcUOFUBIzx4Z0rjs162BA
    - type: loss
      value: 5.004334926605225
      name: loss
      verified: true
      verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiODNjMzI5N2IwNDExOWQzMWYxMzE4YzkxYWYxZmRkNTA2NWQ1MmYzOTFjODJhNGUzODQxYmNkODBlZDA0MGNmZCIsInZlcnNpb24iOjF9.xGNlloXeHra0K5DTKXbsrrkyuAvFXZwjzkxOyjtpw2jWs0KPw4nQ1MKkJiX6juXtleJrvS2u1FQcwCbygUmLDQ
    - type: gen_len
      value: 89.4354
      name: gen_len
      verified: true
      verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiYjBlODBiMmEwN2UzYzE5NTE3ODBkNDVmMTgxMzhlYmVmZjgxMzJjYTBlYjBhMDgzNzhhMWQ0Mzc2MjdjN2E0ZiIsInZlcnNpb24iOjF9.Z9kytQDiNK-TCaHz-0YZeH8FCrW5D0SA-ji7Q86wqdhBC9jTDmJGnBll6mGFcHipERrRKZb12hYStKJanb3iBA
---


# tglobal-large-booksum-WIP

> this is a WIP checkpoint that has been fine-tuned from the vanilla (original) for 10ish epochs. It is **not ready to be used for inference**

This model is a fine-tuned version of [google/long-t5-tglobal-large](https://huggingface.co/google/long-t5-tglobal-large) on the `kmfoda/booksum` dataset.
It achieves the following results on the evaluation set:
- Loss: 4.9519
- Rouge1: 21.8058
- Rouge2: 2.9343
- Rougel: 10.3717
- Rougelsum: 20.1537
- Gen Len: 106.055

## Model description

Testing fine-tuning only on booksum with 16384/1024 the whole time (vs. previous large WIP checkpoint I made that started from a partially-trained `pubmed` checkpoint)

## Intended uses & limitations

this is a WIP checkpoint that has been fine-tuned from the vanilla (original) for 10ish epochs. It is **not ready to be used for inference**

## Training and evaluation data

This is **only** fine-tuned on booksum (vs. previous large WIP checkpoint I made that started from a partially-trained `pubmed` checkpoint)

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 0.0004
- train_batch_size: 1
- eval_batch_size: 1
- seed: 31060
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 32
- total_train_batch_size: 128
- total_eval_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- num_epochs: 3.0

### Training results

| Training Loss | Epoch | Step | Gen Len | Validation Loss | Rouge1  | Rouge2 | Rougel  | Rougelsum |
|:-------------:|:-----:|:----:|:-------:|:---------------:|:-------:|:------:|:-------:|:---------:|
| 5.0389        | 0.99  | 37   | 219.03  | 5.1884          | 29.995  | 4.4045 | 12.8837 | 27.557    |
| 4.8986        | 1.0   | 75   | 5.1286  | 26.921          | 3.7193  | 11.3605| 25.3492 | 276.005   |
| 4.5928        | 2.0   | 150  | 4.9900  | 26.6667         | 3.7342  | 11.8223| 24.7087 | 178.775   |
| 4.6159        | 3.0   | 225  | 4.9519  | 21.8058         | 2.9343  | 10.3717| 20.1537 | 106.055   |


#### eval in bf16


```
***** eval metrics *****
  epoch                   =        3.0
  eval_gen_len            =    103.075
  eval_loss               =     4.9501
  eval_rouge1             =    21.6345
  eval_rouge2             =      2.877
  eval_rougeL             =     10.386
  eval_rougeLsum          =    20.0148
  eval_runtime            = 0:06:02.75
  eval_samples            =        200
  eval_samples_per_second =      0.551
  eval_steps_per_second   =      0.138
[INFO|trainer.py:2724] 2022-11-27 01:00:
```

### Framework versions

- Transformers 4.25.0.dev0
- Pytorch 1.13.0+cu117
- Datasets 2.6.1
- Tokenizers 0.13.1