Text Classification
Transformers
TensorBoard
Safetensors
Spanish
bert
Generated from Trainer
Eval Results (legacy)
Instructions to use jpherrerap/fake-news-bert-base-spanish-wwm-cased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jpherrerap/fake-news-bert-base-spanish-wwm-cased with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="jpherrerap/fake-news-bert-base-spanish-wwm-cased")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("jpherrerap/fake-news-bert-base-spanish-wwm-cased") model = AutoModelForSequenceClassification.from_pretrained("jpherrerap/fake-news-bert-base-spanish-wwm-cased", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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| "best_metric": 0.8378378378378378, | |
| "best_model_checkpoint": "models/fake-news-bert-base-spanish-wwm-cased/checkpoint-140", | |
| "epoch": 2.0, | |
| "eval_steps": 500, | |
| "global_step": 140, | |
| "is_hyper_param_search": false, | |
| "is_local_process_zero": true, | |
| "is_world_process_zero": true, | |
| "log_history": [ | |
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| "epoch": 1.0, | |
| "grad_norm": 6.333802223205566, | |
| "learning_rate": 1.0142857142857143e-05, | |
| "loss": 0.5238, | |
| "step": 70 | |
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| "epoch": 1.0, | |
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| "eval_runtime": 4.1419, | |
| "eval_samples_per_second": 57.944, | |
| "eval_steps_per_second": 3.621, | |
| "step": 70 | |
| }, | |
| { | |
| "epoch": 2.0, | |
| "grad_norm": 15.530929565429688, | |
| "learning_rate": 1.4285714285714287e-07, | |
| "loss": 0.2693, | |
| "step": 140 | |
| }, | |
| { | |
| "epoch": 2.0, | |
| "eval_f1": 0.8378378378378378, | |
| "eval_loss": 0.3234243392944336, | |
| "eval_runtime": 4.0599, | |
| "eval_samples_per_second": 59.114, | |
| "eval_steps_per_second": 3.695, | |
| "step": 140 | |
| }, | |
| { | |
| "epoch": 2.0, | |
| "step": 140, | |
| "total_flos": 589368764006400.0, | |
| "train_loss": 0.39655887058803013, | |
| "train_runtime": 130.5105, | |
| "train_samples_per_second": 17.163, | |
| "train_steps_per_second": 1.073 | |
| } | |
| ], | |
| "logging_steps": 500, | |
| "max_steps": 140, | |
| "num_input_tokens_seen": 0, | |
| "num_train_epochs": 2, | |
| "save_steps": 500, | |
| "stateful_callbacks": { | |
| "TrainerControl": { | |
| "args": { | |
| "should_epoch_stop": false, | |
| "should_evaluate": false, | |
| "should_log": false, | |
| "should_save": true, | |
| "should_training_stop": true | |
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| "attributes": {} | |
| } | |
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| "train_batch_size": 16, | |
| "trial_name": null, | |
| "trial_params": null | |
| } | |