--- license: mit tags: - generated_from_trainer metrics: - accuracy model-index: - name: yt_videos_comments results: [] --- # 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 and usage This model can create a comment on a provided Youtube video title. To test this model you can visit [space](https://huggingface.co/spaces/parseny/youtube_comment_generation) but most likely it is down due to tariffs of hosting. You also can check how the model works in the Inference API, just insert the Youtube video title. ## Intended uses & limitations More information needed ## Training and evaluation data Dataset consisted of English Youtube videos titles and comments to them. Dataset link [US_Video_Comment](https://huggingface.co/datasets/parseny/US_Video_Comment) ## 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