Instructions to use whitedevil0089devil/roberta_base_1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use whitedevil0089devil/roberta_base_1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="whitedevil0089devil/roberta_base_1")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("whitedevil0089devil/roberta_base_1") model = AutoModelForSequenceClassification.from_pretrained("whitedevil0089devil/roberta_base_1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Upload checkpoint-200/trainer_state.json
Browse files
checkpoint-200/trainer_state.json
ADDED
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{
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"best_global_step": 200,
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"best_metric": 0.9943728018757327,
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"best_model_checkpoint": "/content/drive/MyDrive/model/roberta_model/checkpoint-200",
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"epoch": 0.04689331770222743,
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"eval_steps": 200,
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"global_step": 200,
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"is_hyper_param_search": false,
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"is_local_process_zero": true,
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"is_world_process_zero": true,
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"log_history": [
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{
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"epoch": 0.00023446658851113716,
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"grad_norm": 7.900483131408691,
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"learning_rate": 0.0,
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"loss": 1.2285,
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"step": 1
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},
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{
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"epoch": 0.023446658851113716,
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"grad_norm": 2.4035584926605225,
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"learning_rate": 2.9015240328253227e-06,
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"loss": 0.9217,
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"step": 100
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},
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{
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"epoch": 0.04689331770222743,
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"grad_norm": 0.31396016478538513,
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"learning_rate": 5.832356389214537e-06,
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"loss": 0.073,
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"step": 200
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},
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{
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"epoch": 0.04689331770222743,
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"eval_accuracy": 0.9943728018757327,
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"eval_f1_macro": 0.24929461556548319,
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"eval_f1_weighted": 0.9915671414895327,
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"eval_loss": 0.04064385965466499,
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"eval_runtime": 57.486,
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"eval_samples_per_second": 148.384,
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"eval_steps_per_second": 9.289,
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"step": 200
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}
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],
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"logging_steps": 100,
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"max_steps": 17060,
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"num_input_tokens_seen": 0,
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"num_train_epochs": 4,
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"save_steps": 200,
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"stateful_callbacks": {
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"EarlyStoppingCallback": {
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"args": {
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"early_stopping_patience": 3,
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"early_stopping_threshold": 0.001
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},
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"attributes": {
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"early_stopping_patience_counter": 0
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}
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},
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"TrainerControl": {
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"args": {
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"should_epoch_stop": false,
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"should_evaluate": false,
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"should_log": false,
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"should_save": true,
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"should_training_stop": false
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},
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"attributes": {}
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}
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},
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"total_flos": 631483541913600.0,
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"train_batch_size": 16,
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"trial_name": null,
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"trial_params": null
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}
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