eval_results.json

{
    "epoch": 200.0,
    "eval_accuracy": 73.80952380952381,
    "eval_average_metrics": 74.6564932359258,
    "eval_classification_report": "{\"0\": {\"precision\": 0.8571428571428571, \"recall\": 0.7692307692307693, \"f1-score\": 0.8108108108108107, \"support\": 39.0}, \"1\": {\"precision\": 0.5625, \"recall\": 0.5625, \"f1-score\": 0.5625, \"support\": 16.0}, \"2\": {\"precision\": 0.35294117647058826, \"recall\": 0.42857142857142855, \"f1-score\": 0.3870967741935484, \"support\": 14.0}, \"3\": {\"precision\": 0.7647058823529411, \"recall\": 0.8666666666666667, \"f1-score\": 0.8125, \"support\": 15.0}, \"4\": {\"precision\": 0.9090909090909091, \"recall\": 0.9090909090909091, \"f1-score\": 0.9090909090909091, \"support\": 11.0}, \"5\": {\"precision\": 0.8181818181818182, \"recall\": 0.75, \"f1-score\": 0.7826086956521738, \"support\": 12.0}, \"6\": {\"precision\": 0.8888888888888888, \"recall\": 0.8888888888888888, \"f1-score\": 0.8888888888888888, \"support\": 9.0}, \"7\": {\"precision\": 0.75, \"recall\": 0.75, \"f1-score\": 0.75, \"support\": 8.0}, \"8\": {\"precision\": 1.0, \"recall\": 1.0, \"f1-score\": 1.0, \"support\": 2.0}, \"micro avg\": {\"precision\": 0.7380952380952381, \"recall\": 0.7380952380952381, \"f1-score\": 0.7380952380952381, \"support\": 126.0}, \"macro avg\": {\"precision\": 0.7670501702364447, \"recall\": 0.7694387402720735, \"f1-score\": 0.7670551198484813, \"support\": 126.0}, \"weighted avg\": {\"precision\": 0.7512580789891715, \"recall\": 0.7380952380952381, \"f1-score\": 0.7430141333980744, \"support\": 126.0}, \"samples avg\": {\"precision\": 0.7380952380952381, \"recall\": 0.7380952380952381, \"f1-score\": 0.7380952380952381, \"support\": 126.0}}",
    "eval_f1_macro": 76.70551198484813,
    "eval_f1_micro": 73.80952380952381,
    "eval_f1_weighted": 74.30141333980744,
    "eval_loss": 0.5168728828430176,
    "eval_runtime": 1.9516,
    "eval_samples_per_second": 64.563
}