assignment1_Hamza_Distil
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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: 0.9415
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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: 0.1347
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- Accuracy: 0.9415
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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: 3e-05
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- train_batch_size: 32
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- eval_batch_size: 32
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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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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|
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| 0.5065 | 1.0 | 500 | 0.1818 | 0.932 |
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| 0.1474 | 2.0 | 1000 | 0.1347 | 0.9415 |
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### Framework versions
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- Transformers 4.38.2
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- Pytorch 2.1.0+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:e972f53e6ce041763403f8decf20a732e8d45bdc9bf0260961c636c4563b7cfd
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size 267844872
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runs/Mar10_01-18-36_74a7c39da0ee/events.out.tfevents.1710033516.74a7c39da0ee.843.0
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version https://git-lfs.github.com/spec/v1
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oid sha256:b3b58ae8e619780f798acb2d2bbc74c0db1fa7259a1b080155775f292bc77867
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size 6113
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runs/Mar10_01-18-36_74a7c39da0ee/events.out.tfevents.1710035005.74a7c39da0ee.843.1
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version https://git-lfs.github.com/spec/v1
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oid sha256:9a52464ddaa2fbba33061b7de6b11cb7345e2f0231fe35934547ce738afc22f4
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size 1057
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training_args.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:6f0d4e5d39de1d471fcc67fcae9bb2fb561262e3f913729cb43bd36ad147388a
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size 4856
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