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Hamzas_assignment1_Albert2
Browse files- README.md +76 -0
- config.json +50 -0
- model.safetensors +3 -0
- runs/Mar10_21-11-06_9a1eb7cd3361/events.out.tfevents.1710105137.9a1eb7cd3361.406.0 +3 -0
- runs/Mar10_21-43-42_9a1eb7cd3361/events.out.tfevents.1710107092.9a1eb7cd3361.9018.0 +3 -0
- runs/Mar10_21-43-42_9a1eb7cd3361/events.out.tfevents.1710111221.9a1eb7cd3361.9018.1 +3 -0
- training_args.bin +3 -0
README.md
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---
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license: apache-2.0
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base_model: albert-base-v2
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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: AlbertResults2
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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: 0.931
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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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# AlbertResults2
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This model is a fine-tuned version of [albert-base-v2](https://huggingface.co/albert-base-v2) on the emotion dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.1619
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- Accuracy: 0.931
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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: 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: 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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| 0.3348 | 1.0 | 1000 | 0.2663 | 0.9075 |
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| 0.1566 | 2.0 | 2000 | 0.1619 | 0.931 |
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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": "albert-base-v2",
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"architectures": [
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"AlbertForSequenceClassification"
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],
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"attention_probs_dropout_prob": 0,
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"bos_token_id": 2,
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"classifier_dropout_prob": 0.1,
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"down_scale_factor": 1,
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"embedding_size": 128,
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"eos_token_id": 3,
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"gap_size": 0,
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"hidden_act": "gelu_new",
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"hidden_dropout_prob": 0,
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"hidden_size": 768,
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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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"inner_group_num": 1,
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"intermediate_size": 3072,
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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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"layer_norm_eps": 1e-12,
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"max_position_embeddings": 512,
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"model_type": "albert",
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"net_structure_type": 0,
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"num_attention_heads": 12,
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"num_hidden_groups": 1,
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"num_hidden_layers": 12,
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"num_memory_blocks": 0,
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"pad_token_id": 0,
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"position_embedding_type": "absolute",
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"problem_type": "single_label_classification",
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"torch_dtype": "float32",
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"transformers_version": "4.38.2",
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"type_vocab_size": 2,
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"vocab_size": 30000
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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 sha256:08c7bd9e31cfdf70ac8b0107b98d55009b44abd2eb0e4fb408cf08904ca47ee5
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size 46756216
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runs/Mar10_21-11-06_9a1eb7cd3361/events.out.tfevents.1710105137.9a1eb7cd3361.406.0
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version https://git-lfs.github.com/spec/v1
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oid sha256:723db79ce896e3ebf84aba2a478cba15ae19085240f3629884d16e8796ed8cb0
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size 10760
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runs/Mar10_21-43-42_9a1eb7cd3361/events.out.tfevents.1710107092.9a1eb7cd3361.9018.0
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version https://git-lfs.github.com/spec/v1
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oid sha256:8c4ae18bc096652191ff1caba8b9992b12e0feb1cff5ec3bbfe056558d4c4170
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size 7655
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runs/Mar10_21-43-42_9a1eb7cd3361/events.out.tfevents.1710111221.9a1eb7cd3361.9018.1
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version https://git-lfs.github.com/spec/v1
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oid sha256:7b1b3bef87c1127141a94281f83609cf37fc96a5d4278a0ede815b5b30322255
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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:c2dfc1a30fccfc3cc690b90737598e4a16e5c30142a4e56546c572102e0509bb
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size 4920
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