Instructions to use mllm-dev/merge_diff_data_IMDB with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mllm-dev/merge_diff_data_IMDB with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="mllm-dev/merge_diff_data_IMDB")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("mllm-dev/merge_diff_data_IMDB") model = AutoModelForSequenceClassification.from_pretrained("mllm-dev/merge_diff_data_IMDB", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "best_metric": 0.1659126728773117, | |
| "best_model_checkpoint": "imdb_full/checkpoint-393", | |
| "epoch": 3.0, | |
| "eval_steps": 500, | |
| "global_step": 393, | |
| "is_hyper_param_search": false, | |
| "is_local_process_zero": true, | |
| "is_world_process_zero": true, | |
| "log_history": [ | |
| { | |
| "epoch": 1.0, | |
| "eval_accuracy": 0.9204, | |
| "eval_loss": 0.21770058572292328, | |
| "eval_runtime": 78.2774, | |
| "eval_samples_per_second": 319.377, | |
| "eval_steps_per_second": 1.674, | |
| "step": 131 | |
| }, | |
| { | |
| "epoch": 2.0, | |
| "eval_accuracy": 0.92204, | |
| "eval_loss": 0.19915565848350525, | |
| "eval_runtime": 78.1566, | |
| "eval_samples_per_second": 319.871, | |
| "eval_steps_per_second": 1.676, | |
| "step": 262 | |
| }, | |
| { | |
| "epoch": 3.0, | |
| "eval_accuracy": 0.93932, | |
| "eval_loss": 0.1659126728773117, | |
| "eval_runtime": 78.3631, | |
| "eval_samples_per_second": 319.028, | |
| "eval_steps_per_second": 1.672, | |
| "step": 393 | |
| } | |
| ], | |
| "logging_steps": 500, | |
| "max_steps": 655, | |
| "num_input_tokens_seen": 0, | |
| "num_train_epochs": 5, | |
| "save_steps": 500, | |
| "total_flos": 3.917961459125453e+16, | |
| "train_batch_size": 192, | |
| "trial_name": null, | |
| "trial_params": null | |
| } | |