Instructions to use shenkha/DGSlow_Bartbase_PC with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use shenkha/DGSlow_Bartbase_PC with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("shenkha/DGSlow_Bartbase_PC") model = AutoModelForSeq2SeqLM.from_pretrained("shenkha/DGSlow_Bartbase_PC", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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| "best_metric": null, | |
| "best_model_checkpoint": null, | |
| "epoch": 49.98360655737705, | |
| "global_step": 2400, | |
| "is_hyper_param_search": false, | |
| "is_local_process_zero": true, | |
| "is_world_process_zero": true, | |
| "log_history": [ | |
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| "epoch": 10.41, | |
| "learning_rate": 3.958333333333333e-05, | |
| "loss": 2.9289, | |
| "step": 500 | |
| }, | |
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| "epoch": 20.82, | |
| "learning_rate": 2.916666666666667e-05, | |
| "loss": 2.5801, | |
| "step": 1000 | |
| }, | |
| { | |
| "epoch": 31.25, | |
| "learning_rate": 1.8750000000000002e-05, | |
| "loss": 2.3955, | |
| "step": 1500 | |
| }, | |
| { | |
| "epoch": 41.66, | |
| "learning_rate": 8.333333333333334e-06, | |
| "loss": 2.2678, | |
| "step": 2000 | |
| }, | |
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| "step": 2400, | |
| "total_flos": 2.9654605052706816e+17, | |
| "train_loss": 2.4875941975911458, | |
| "train_runtime": 37059.0269, | |
| "train_samples_per_second": 84.247, | |
| "train_steps_per_second": 0.065 | |
| } | |
| ], | |
| "max_steps": 2400, | |
| "num_train_epochs": 50, | |
| "total_flos": 2.9654605052706816e+17, | |
| "trial_name": null, | |
| "trial_params": null | |
| } | |