End of training

README.md

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+---
+base_model: cardiffnlp/twitter-xlm-roberta-base-sentiment-multilingual
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: sentiment_analysis_model_rpsi
+ results: []
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/themohal/huggingface/runs/ddp65niu)
+# sentiment_analysis_model_rpsi
+
+This model is a fine-tuned version of [cardiffnlp/twitter-xlm-roberta-base-sentiment-multilingual](https://huggingface.co/cardiffnlp/twitter-xlm-roberta-base-sentiment-multilingual) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.5686
+- Accuracy: 0.8018
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 2e-05
+- train_batch_size: 32
+- eval_batch_size: 32
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 6
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:-----:|:---------------:|:--------:|
+| 0.7314 | 1.0 | 3378 | 0.6028 | 0.7367 |
+| 0.563 | 2.0 | 6756 | 0.5503 | 0.7646 |
+| 0.4859 | 3.0 | 10134 | 0.5316 | 0.7847 |
+| 0.421 | 4.0 | 13512 | 0.5223 | 0.7954 |
+| 0.3668 | 5.0 | 16890 | 0.5514 | 0.7973 |
+| 0.3266 | 6.0 | 20268 | 0.5686 | 0.8018 |
+
+
+### Framework versions
+
+- Transformers 4.42.3
+- Pytorch 2.1.2
+- Datasets 2.20.0
+- Tokenizers 0.19.1

config.json

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+{
+ "_name_or_path": "cardiffnlp/twitter-xlm-roberta-base-sentiment-multilingual",
+ "architectures": [
+ "XLMRobertaForSequenceClassification"
+ ],
+ "attention_probs_dropout_prob": 0.1,
+ "bos_token_id": 0,
+ "classifier_dropout": null,
+ "eos_token_id": 2,
+ "gradient_checkpointing": false,
+ "hidden_act": "gelu",
+ "hidden_dropout_prob": 0.1,
+ "hidden_size": 768,
+ "id2label": {
+ "0": "negative",
+ "1": "neutral",
+ "2": "positive"
+ },
+ "initializer_range": 0.02,
+ "intermediate_size": 3072,
+ "label2id": {
+ "negative": 0,
+ "neutral": 1,
+ "positive": 2
+ },
+ "layer_norm_eps": 1e-05,
+ "max_position_embeddings": 514,
+ "model_type": "xlm-roberta",
+ "num_attention_heads": 12,
+ "num_hidden_layers": 12,
+ "output_past": true,
+ "pad_token_id": 1,
+ "position_embedding_type": "absolute",
+ "problem_type": "single_label_classification",
+ "torch_dtype": "float32",
+ "transformers_version": "4.42.3",
+ "type_vocab_size": 1,
+ "use_cache": true,
+ "vocab_size": 250002
+}

model.safetensors

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runs/Aug27_23-13-35_90dd27a1bf53/events.out.tfevents.1724800424.90dd27a1bf53.23.0

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runs/Aug27_23-13-35_90dd27a1bf53/events.out.tfevents.1724841990.90dd27a1bf53.23.1

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special_tokens_map.json

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+{
+ "cls_token": "[CLS]",
+ "mask_token": "[MASK]",
+ "pad_token": "[PAD]",
+ "sep_token": "[SEP]",
+ "unk_token": "[UNK]"
+}

tokenizer_config.json

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+{
+ "added_tokens_decoder": {
+ "0": {
+ "content": "[PAD]",
+ "lstrip": false,
+ "normalized": false,
+ "rstrip": false,
+ "single_word": false,
+ "special": true
+ },
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+ "lstrip": false,
+ "normalized": false,
+ "rstrip": false,
+ "single_word": false,
+ "special": true
+ }
+ },
+ "clean_up_tokenization_spaces": true,
+ "cls_token": "[CLS]",
+ "do_basic_tokenize": true,
+ "do_lower_case": false,
+ "lowercase": false,
+ "mask_token": "[MASK]",
+ "model_max_length": 512,
+ "never_split": null,
+ "pad_token": "[PAD]",
+ "sep_token": "[SEP]",
+ "strip_accents": false,
+ "tokenize_chinese_chars": true,
+ "tokenizer_class": "BertTokenizer",
+ "unk_token": "[UNK]"
+}

training_args.bin

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