adelinachirtes
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Training in progress epoch 0
Browse files- README.md +15 -21
- config.json +0 -2
- tf_model.h5 +3 -0
README.md
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license: apache-2.0
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base_model: distilbert/distilbert-base-uncased
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tags:
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metrics:
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- accuracy
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model-index:
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- name: my_awesome_model
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results: []
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---
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<!-- This model card has been generated automatically according to the information
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# my_awesome_model
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This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-base-uncased) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.
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## Model description
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 2e-05
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- eval_batch_size: 16
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- num_epochs: 2
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### Training results
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| 0.1467 | 2.0 | 3126 | 0.2309 | 0.9312 |
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### Framework versions
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- Transformers 4.41.1
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- Datasets 2.19.1
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- Tokenizers 0.19.1
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license: apache-2.0
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base_model: distilbert/distilbert-base-uncased
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tags:
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- generated_from_keras_callback
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model-index:
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- name: adelinachirtes/my_awesome_model
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results: []
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---
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<!-- This model card has been generated automatically according to the information Keras had access to. You should
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probably proofread and complete it, then remove this comment. -->
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# adelinachirtes/my_awesome_model
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This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-base-uncased) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Train Loss: 0.2559
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- Validation Loss: 0.1899
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- Train Accuracy: 0.9283
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- Epoch: 0
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## Model description
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### Training hyperparameters
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The following hyperparameters were used during training:
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- 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': True, 'is_legacy_optimizer': False, 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 7810, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}
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- training_precision: float32
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### Training results
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| Train Loss | Validation Loss | Train Accuracy | Epoch |
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|:----------:|:---------------:|:--------------:|:-----:|
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| 0.2559 | 0.1899 | 0.9283 | 0 |
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### Framework versions
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- Transformers 4.41.1
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- TensorFlow 2.15.0
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- Datasets 2.19.1
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- Tokenizers 0.19.1
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config.json
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"n_heads": 12,
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"n_layers": 6,
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"pad_token_id": 0,
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"problem_type": "single_label_classification",
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"qa_dropout": 0.1,
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"seq_classif_dropout": 0.2,
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"sinusoidal_pos_embds": false,
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"tie_weights_": true,
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"torch_dtype": "float32",
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"transformers_version": "4.41.1",
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"vocab_size": 30522
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}
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"n_heads": 12,
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"n_layers": 6,
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"pad_token_id": 0,
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"qa_dropout": 0.1,
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"seq_classif_dropout": 0.2,
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"sinusoidal_pos_embds": false,
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"tie_weights_": true,
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"transformers_version": "4.41.1",
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"vocab_size": 30522
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}
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tf_model.h5
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version https://git-lfs.github.com/spec/v1
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oid sha256:5016ed931f7fb13c198779f498087f9e51c442778ba8e0c779b8e0127da3ddc4
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size 267951808
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