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---
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: yt_videos_comments
results: []
---
<!-- 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. -->
# youtube video comment generation
This model is a fine-tuned version of [gpt2-large](https://huggingface.co/gpt2-large) on the [US_Video_Comment](https://huggingface.co/datasets/parseny/US_Video_Comment) dataset.
It achieves the following results on the evaluation set:
- Loss: 2.0918
- Accuracy: 0.6277
## 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: 1e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- total_eval_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 2000
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.1201 | 1.53 | 500 | 2.1152 | 0.6220 |
| 2.016 | 3.07 | 1000 | 2.0957 | 0.6254 |
| 1.9383 | 4.6 | 1500 | 2.0898 | 0.6271 |
| 1.8823 | 6.14 | 2000 | 2.0918 | 0.6277 |
### Framework versions
- Transformers 4.29.0.dev0
- Pytorch 2.0.0-rc1
- Datasets 2.11.0
- Tokenizers 0.13.3
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