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End of training
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README.md
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---
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license: apache-2.0
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base_model: distilbert-base-uncased
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tags:
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- generated_from_trainer
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datasets:
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- emotion
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metrics:
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- accuracy
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model-index:
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- name: results
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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: emotion
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type: emotion
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config: split
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split: validation
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args: split
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.929
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# results
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This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the emotion dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.1691
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- Accuracy: 0.929
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 5e-05
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- train_batch_size: 16
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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: 3
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|
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| 0.2358 | 1.0 | 1000 | 0.1881 | 0.928 |
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| 0.1301 | 2.0 | 2000 | 0.1721 | 0.936 |
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| 0.0806 | 3.0 | 3000 | 0.1738 | 0.94 |
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### Framework versions
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- Transformers 4.38.2
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- Pytorch 2.2.1+cu121
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- Datasets 2.18.0
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- Tokenizers 0.15.2
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config.json
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{
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"_name_or_path": "distilbert-base-uncased",
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"activation": "gelu",
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"architectures": [
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"DistilBertForSequenceClassification"
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],
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"attention_dropout": 0.1,
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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": "LABEL_0",
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"1": "LABEL_1",
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"2": "LABEL_2",
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"3": "LABEL_3",
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"4": "LABEL_4",
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"5": "LABEL_5"
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},
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"initializer_range": 0.02,
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"label2id": {
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"LABEL_0": 0,
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"LABEL_1": 1,
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"LABEL_2": 2,
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"LABEL_3": 3,
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"LABEL_4": 4,
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"LABEL_5": 5
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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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"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": "4.38.2",
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"vocab_size": 30522
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}
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:6c9abd8422e819724c53239bdbb1a757f0bd74639bdc435da3cb1bcb852721c3
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size 267844872
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runs/Mar05_22-56-00_81c07d030f6d/events.out.tfevents.1709679403.81c07d030f6d.619.0
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version https://git-lfs.github.com/spec/v1
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size 7587
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runs/Mar05_22-56-00_81c07d030f6d/events.out.tfevents.1709681863.81c07d030f6d.619.1
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version https://git-lfs.github.com/spec/v1
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size 411
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training_args.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:972b151b4fbd86884974e6e1b60e9e5d49d86a2c8913192bf6b048ba2500ab27
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size 4856
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