End of training
Browse files- README.md +64 -0
- config.json +39 -0
- model.safetensors +3 -0
- runs/Nov01_07-18-41_cefd2920e282/events.out.tfevents.1698823140.cefd2920e282.2664.0 +3 -0
- runs/Nov02_17-35-58_854bbcebb551/events.out.tfevents.1698946571.854bbcebb551.1245.0 +3 -0
- runs/Nov02_17-35-58_854bbcebb551/events.out.tfevents.1698949334.854bbcebb551.1245.1 +3 -0
- runs/Nov06_22-37-46_6c8330291840/events.out.tfevents.1699310280.6c8330291840.588.0 +3 -0
- runs/Nov07_18-23-11_f7861474fc09/events.out.tfevents.1699381467.f7861474fc09.1396.0 +3 -0
- runs/Nov07_19-34-48_9c10e3e529f3/events.out.tfevents.1699386111.9c10e3e529f3.294.0 +3 -0
- runs/Nov08_21-38-47_9b5eff9f4724/events.out.tfevents.1699479537.9b5eff9f4724.469.0 +3 -0
- runs/Nov09_11-43-58_b5c41c6ea59a/events.out.tfevents.1699530251.b5c41c6ea59a.617.0 +3 -0
- runs/Nov09_19-19-27_5c95ed4ca3fd/events.out.tfevents.1699557576.5c95ed4ca3fd.4647.0 +3 -0
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- runs/Nov10_22-09-26_8411bb85556b/events.out.tfevents.1699654176.8411bb85556b.629.0 +3 -0
- runs/Nov10_22-09-26_8411bb85556b/events.out.tfevents.1699655574.8411bb85556b.629.1 +3 -0
- training_args.bin +3 -0
README.md
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---
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base_model: cardiffnlp/twitter-roberta-base-sentiment-latest
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tags:
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- generated_from_trainer
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metrics:
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- accuracy
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model-index:
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- name: output
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results: []
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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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# output
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This model is a fine-tuned version of [cardiffnlp/twitter-roberta-base-sentiment-latest](https://huggingface.co/cardiffnlp/twitter-roberta-base-sentiment-latest) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.5333
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- Accuracy: 0.786
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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: 8
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- eval_batch_size: 8
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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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| 0.7137 | 0.5 | 500 | 0.6020 | 0.7675 |
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| 0.6209 | 1.0 | 1000 | 0.5333 | 0.786 |
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| 0.4622 | 1.5 | 1500 | 0.6210 | 0.792 |
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| 0.4764 | 2.0 | 2000 | 0.7468 | 0.783 |
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| 0.3036 | 2.5 | 2500 | 0.8896 | 0.795 |
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| 0.2941 | 3.0 | 3000 | 0.8803 | 0.8035 |
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### Framework versions
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- Transformers 4.35.0
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- Pytorch 2.1.0+cu118
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- Datasets 2.14.6
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- Tokenizers 0.14.1
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config.json
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{
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"_name_or_path": "cardiffnlp/twitter-roberta-base-sentiment-latest",
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"architectures": [
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"RobertaForSequenceClassification"
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],
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"attention_probs_dropout_prob": 0.1,
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"bos_token_id": 0,
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"classifier_dropout": null,
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"eos_token_id": 2,
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"gradient_checkpointing": false,
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"hidden_act": "gelu",
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"hidden_dropout_prob": 0.1,
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"hidden_size": 768,
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"id2label": {
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"0": "negative",
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"1": "neutral",
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"2": "positive"
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},
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"initializer_range": 0.02,
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"intermediate_size": 3072,
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"label2id": {
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"negative": 0,
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"neutral": 1,
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"positive": 2
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},
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"layer_norm_eps": 1e-05,
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"max_position_embeddings": 514,
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"model_type": "roberta",
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"num_attention_heads": 12,
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"num_hidden_layers": 12,
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"pad_token_id": 1,
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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": "4.35.0",
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"type_vocab_size": 1,
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"use_cache": true,
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"vocab_size": 50265
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}
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