JavierAnd/cliente360_class_weighted_model

1---2tags:3- generated_from_keras_callback4model-index:5- name: JavierAnd/cliente360_class_weighted_model6  results: []7---8 9<!-- This model card has been generated automatically according to the information Keras had access to. You should10probably proofread and complete it, then remove this comment. -->11 12# JavierAnd/cliente360_class_weighted_model13 14This model is a fine-tuned version of [dccuchile/distilbert-base-spanish-uncased](https://huggingface.co/dccuchile/distilbert-base-spanish-uncased) on an unknown dataset.15It achieves the following results on the evaluation set:16- Train Loss: 0.840017- Validation Loss: 0.863218- Train F1: 0.741919- Epoch: 120 21## Model description22 23More information needed24 25## Intended uses & limitations26 27More information needed28 29## Training and evaluation data30 31More information needed32 33## Training procedure34 35### Training hyperparameters36 37The following hyperparameters were used during training:38- optimizer: {'name': 'Adam', 'weight_decay': None, 'clipnorm': None, 'global_clipnorm': None, 'clipvalue': None, 'use_ema': False, 'ema_momentum': 0.99, 'ema_overwrite_frequency': None, 'jit_compile': False, 'is_legacy_optimizer': False, 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 16071, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}}, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}39- training_precision: float3240 41### Training results42 43| Train Loss | Validation Loss | Train F1 | Epoch |44|:----------:|:---------------:|:--------:|:-----:|45| 1.2011     | 0.9435          | 0.7152   | 0     |46| 0.8400     | 0.8632          | 0.7419   | 1     |47 48 49### Framework versions50 51- Transformers 4.27.352- TensorFlow 2.12.053- Datasets 2.11.054- Tokenizers 0.13.255