Text Classification
Transformers
Safetensors
deberta
deberta-v3
multiple-choice
question-answering
awp
Instructions to use dahaludba/QSolver_Encoder_V2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dahaludba/QSolver_Encoder_V2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="dahaludba/QSolver_Encoder_V2")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("dahaludba/QSolver_Encoder_V2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "best_global_step": 504, | |
| "best_metric": 0.9870483980913429, | |
| "best_model_checkpoint": "./deberta_v3_fold_3/checkpoint-504", | |
| "epoch": 4.0, | |
| "eval_steps": 500, | |
| "global_step": 504, | |
| "is_hyper_param_search": false, | |
| "is_local_process_zero": true, | |
| "is_world_process_zero": true, | |
| "log_history": [ | |
| { | |
| "epoch": 1.0, | |
| "eval_loss": 1.132867455482483, | |
| "eval_map@3": 0.7177914110429446, | |
| "eval_runtime": 66.7481, | |
| "eval_samples_per_second": 7.326, | |
| "eval_steps_per_second": 7.326, | |
| "step": 126 | |
| }, | |
| { | |
| "epoch": 2.0, | |
| "eval_loss": 0.11986057460308075, | |
| "eval_map@3": 0.9795501022494887, | |
| "eval_runtime": 67.9102, | |
| "eval_samples_per_second": 7.201, | |
| "eval_steps_per_second": 7.201, | |
| "step": 252 | |
| }, | |
| { | |
| "epoch": 3.0, | |
| "eval_loss": 0.06871046870946884, | |
| "eval_map@3": 0.985344239945467, | |
| "eval_runtime": 68.3125, | |
| "eval_samples_per_second": 7.158, | |
| "eval_steps_per_second": 7.158, | |
| "step": 378 | |
| }, | |
| { | |
| "epoch": 3.970661362506216, | |
| "grad_norm": 153.56666564941406, | |
| "learning_rate": 2.1962072489860595e-09, | |
| "loss": 9.9226845703125, | |
| "step": 500 | |
| }, | |
| { | |
| "epoch": 4.0, | |
| "eval_loss": 0.0618998222053051, | |
| "eval_map@3": 0.9870483980913429, | |
| "eval_runtime": 66.6534, | |
| "eval_samples_per_second": 7.336, | |
| "eval_steps_per_second": 7.336, | |
| "step": 504 | |
| } | |
| ], | |
| "logging_steps": 500, | |
| "max_steps": 504, | |
| "num_input_tokens_seen": 0, | |
| "num_train_epochs": 4, | |
| "save_steps": 500, | |
| "stateful_callbacks": { | |
| "TrainerControl": { | |
| "args": { | |
| "should_epoch_stop": false, | |
| "should_evaluate": false, | |
| "should_log": false, | |
| "should_save": true, | |
| "should_training_stop": true | |
| }, | |
| "attributes": {} | |
| } | |
| }, | |
| "total_flos": 4520100776172240.0, | |
| "train_batch_size": 1, | |
| "trial_name": null, | |
| "trial_params": null | |
| } | |