Instructions to use kumarabd1996/agent-task-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Laya
How to use kumarabd1996/agent-task-classifier with Laya:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
Download train_report.json from kumarabd1996/agent-task-classifier: direct link, hf CLI and curl.
- Browser
- Download file 2.49 kB
-
https://huggingface.co/kumarabd1996/agent-task-classifier/resolve/main/train_report.json
- Command line
-
hf download hf://kumarabd1996/agent-task-classifier/train_report.json
-
curl -L -o train_report.json https://huggingface.co/kumarabd1996/agent-task-classifier/resolve/main/train_report.json
2.49 kB
| { | |
| "eval_source": "corpus_v2/eval.jsonl", | |
| "eval_mode": "held_out", | |
| "is_held_out": true, | |
| "eval_items": 54, | |
| "note": "Metrics reflect independent held-out evaluation.", | |
| "before": { | |
| "items": 54, | |
| "loss": 1.8596, | |
| "accuracy": 0.2407, | |
| "mean_confidence": 0.3148, | |
| "ece": 0.1869, | |
| "brier": 0.7831, | |
| "brier_top1": 0.1308, | |
| "by_type": { | |
| "choice": { | |
| "items": 54, | |
| "loss": 1.8596, | |
| "accuracy": 0.2407, | |
| "mean_confidence": 0.3148, | |
| "ece": 0.1869, | |
| "brier": 0.7831, | |
| "brier_top1": 0.1308 | |
| } | |
| } | |
| }, | |
| "after": { | |
| "items": 54, | |
| "loss": 0.6661, | |
| "accuracy": 0.8704, | |
| "mean_confidence": 0.9589, | |
| "ece": 0.0886, | |
| "brier": 0.2397, | |
| "brier_top1": 0.1096, | |
| "by_type": { | |
| "choice": { | |
| "items": 54, | |
| "loss": 0.6661, | |
| "accuracy": 0.8704, | |
| "mean_confidence": 0.9589, | |
| "ece": 0.0886, | |
| "brier": 0.2397, | |
| "brier_top1": 0.1096 | |
| } | |
| } | |
| }, | |
| "comparison": { | |
| "delta_accuracy": 0.6297, | |
| "delta_loss": -1.1935, | |
| "delta_ece": -0.0983, | |
| "delta_brier": -0.5434, | |
| "delta_brier_top1": -0.0212, | |
| "delta_mean_confidence": 0.6441 | |
| }, | |
| "calibration": { | |
| "choice": { | |
| "items": 400, | |
| "temperature": 3.9046413898468018, | |
| "issues": [], | |
| "accuracy": 0.9575, | |
| "mean_confidence": 0.9617928987797445 | |
| }, | |
| "score": { | |
| "items": 0, | |
| "temperature": 1.0, | |
| "issues": [] | |
| }, | |
| "noul": { | |
| "items": 0, | |
| "temperature": 1.0, | |
| "issues": [] | |
| } | |
| }, | |
| "abstention_thresholds": { | |
| "choice:6-10": 0.5204 | |
| }, | |
| "training": { | |
| "epochs": 4, | |
| "micro_batch": 2, | |
| "grad_accum": 32, | |
| "encoder_lr": 2.5e-05, | |
| "head_lr": 0.0001, | |
| "min_lr": 1e-06, | |
| "weight_decay": 0.01, | |
| "grad_clip": 1.0, | |
| "loss": "rlcd", | |
| "rl_samples": 4, | |
| "sigma_start": 0.4, | |
| "sigma_end": 0.1, | |
| "w_sph": 0.75, | |
| "w_rps": 1.0, | |
| "shuffle_options": [ | |
| "choice" | |
| ], | |
| "option_layout": null, | |
| "freeze_encoder": false, | |
| "calib_max": 400, | |
| "calib_frac": 0.1, | |
| "calib_seed": 20260922, | |
| "seed": 0, | |
| "max_len": 256, | |
| "head_max_len": null, | |
| "amp": null, | |
| "gradient_checkpointing": null, | |
| "log_every": 100, | |
| "label_smoothing": 0.0, | |
| "text_column": "text", | |
| "label_column": "label", | |
| "question_id": "label", | |
| "instructions": null, | |
| "eval_data": "corpus_v2/eval.jsonl", | |
| "target_error": 0.1, | |
| "min_abstain_n": 10 | |
| } | |
| } |