Training in progress epoch 0
Browse files
README.md
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---
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license: apache-2.0
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tags:
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datasets:
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- glue
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metrics:
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- accuracy
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model-index:
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- name: distilbert-base-uncased-finetuned-sst2
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results:
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- task:
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name: Text Classification
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type: text-classification
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dataset:
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name: glue
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type: glue
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config: sst2
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split: validation
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args: sst2
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.9128440366972477
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---
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<!-- This model card has been generated automatically according to the information
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# distilbert-base-uncased-finetuned-sst2
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This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on
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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: 5
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### Training results
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| 0.
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| 0.1271 | 2.0 | 8420 | 0.3177 | 0.9128 |
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| 0.0958 | 3.0 | 12630 | 0.3847 | 0.9014 |
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| 0.0582 | 4.0 | 16840 | 0.4434 | 0.9106 |
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| 0.038 | 5.0 | 21050 | 0.5351 | 0.9002 |
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### Framework versions
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- Transformers 4.27.
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-
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- Datasets 2.
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- Tokenizers 0.13.2
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---
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license: apache-2.0
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tags:
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- generated_from_keras_callback
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model-index:
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- name: rwang5688/distilbert-base-uncased-finetuned-sst2
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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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# rwang5688/distilbert-base-uncased-finetuned-sst2
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This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/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: 0.2128
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- Validation Loss: 0.3199
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- Train Accuracy: 0.8784
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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': False, 'is_legacy_optimizer': False, 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 12627, '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}
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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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| 0.2128 | 0.3199 | 0.8784 | 0 |
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### Framework versions
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- Transformers 4.27.4
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- TensorFlow 2.12.0
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- Datasets 2.11.0
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- Tokenizers 0.13.2
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config.json
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"dim": 768,
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"dropout": 0.1,
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"hidden_dim": 3072,
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"initializer_range": 0.02,
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"max_position_embeddings": 512,
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"model_type": "distilbert",
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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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"
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"transformers_version": "4.27.3",
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"vocab_size": 30522
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}
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"dim": 768,
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"dropout": 0.1,
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"hidden_dim": 3072,
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"id2label": {
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"0": "Invalid",
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"1": "Valid"
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},
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"initializer_range": 0.02,
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"label2id": {
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"Invalid": 0,
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"Valid": 1
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},
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"max_position_embeddings": 512,
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"model_type": "distilbert",
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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": "4.27.4",
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"vocab_size": 30522
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}
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logs/train/events.out.tfevents.1681108353.ip-172-26-15-174.6245.0.v2
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logs/train/events.out.tfevents.1681165251.ip-172-26-15-174.3201.0.v2
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logs/validation/events.out.tfevents.1681167150.ip-172-26-15-174.3201.1.v2
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tf_model.h5
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