End of training

README.md

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+---
+base_model: pysentimiento/robertuito-sentiment-analysis
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- precision
+- recall
+model-index:
+- name: roBERTuito-Meta4Types-ft-ES
+  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. -->
+
+# roBERTuito-Meta4Types-ft-ES
+
+This model is a fine-tuned version of [pysentimiento/robertuito-sentiment-analysis](https://huggingface.co/pysentimiento/robertuito-sentiment-analysis) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.8547
+- Roc Auc: 0.6496
+- Hamming Loss: 0.1830
+- F1 Score: 0.5653
+- Accuracy: 0.5931
+- Precision: 0.6214
+- Recall: 0.5298
+
+## 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: 5e-05
+- train_batch_size: 4
+- eval_batch_size: 4
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 500
+- num_epochs: 10
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Roc Auc | Hamming Loss | F1 Score | Accuracy | Precision | Recall |
+|:-------------:|:-----:|:----:|:---------------:|:-------:|:------------:|:--------:|:--------:|:---------:|:------:|
+| No log        | 1.0   | 204  | 0.5044          | 0.5     | 0.2026       | 0.2930   | 0.6176   | 0.9281    | 0.3333 |
+| No log        | 2.0   | 408  | 0.4634          | 0.5717  | 0.1961       | 0.4829   | 0.6225   | 0.5819    | 0.4651 |
+| 0.4697        | 3.0   | 612  | 0.4784          | 0.6173  | 0.1748       | 0.4993   | 0.6275   | 0.8438    | 0.4596 |
+| 0.4697        | 4.0   | 816  | 0.6585          | 0.6129  | 0.2124       | 0.5351   | 0.5539   | 0.5456    | 0.5279 |
+| 0.1464        | 5.0   | 1020 | 0.8070          | 0.5891  | 0.2010       | 0.4963   | 0.6078   | 0.5732    | 0.4703 |
+| 0.1464        | 6.0   | 1224 | 0.7848          | 0.6094  | 0.1912       | 0.5294   | 0.5735   | 0.5916    | 0.4989 |
+| 0.1464        | 7.0   | 1428 | 0.8547          | 0.6496  | 0.1830       | 0.5653   | 0.5931   | 0.6214    | 0.5298 |
+| 0.0278        | 8.0   | 1632 | 0.9068          | 0.6152  | 0.1846       | 0.5396   | 0.5784   | 0.6114    | 0.5064 |
+| 0.0278        | 9.0   | 1836 | 0.9251          | 0.6110  | 0.1961       | 0.5258   | 0.5588   | 0.5674    | 0.5023 |
+| 0.0029        | 10.0  | 2040 | 0.9343          | 0.6146  | 0.1944       | 0.5276   | 0.5686   | 0.5751    | 0.5002 |
+
+
+### Framework versions
+
+- Transformers 4.43.3
+- Pytorch 2.3.1+cu121
+- Datasets 2.20.0
+- Tokenizers 0.19.1

config.json

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+{
+  "_name_or_path": "pysentimiento/robertuito-sentiment-analysis",
+  "architectures": [
+    "RobertaForMultilabelSequenceClassification"
+  ],
+  "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": "NEG",
+    "1": "NEU",
+    "2": "POS"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "NEG": 0,
+    "NEU": 1,
+    "POS": 2
+  },
+  "layer_norm_eps": 1e-12,
+  "max_position_embeddings": 130,
+  "model_type": "roberta",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "pad_token_id": 1,
+  "position_embedding_type": "absolute",
+  "problem_type": "single_label_classification",
+  "torch_dtype": "float32",
+  "transformers_version": "4.43.3",
+  "type_vocab_size": 1,
+  "use_cache": true,
+  "vocab_size": 30002
+}

model.safetensors

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special_tokens_map.json

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+{
+  "bos_token": {
+    "content": "<s>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
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+  "eos_token": {
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+    "lstrip": false,
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+    "single_word": false
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+  "mask_token": {
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+    "lstrip": false,
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+    "single_word": false
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+}

tokenizer_config.json

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+{
+  "added_tokens_decoder": {
+    "0": {
+      "content": "<s>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
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+      "special": true
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+    "30000": {
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+      "single_word": false,
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+    "30001": {
+      "content": "emoji",
+      "lstrip": false,
+      "normalized": true,
+      "rstrip": false,
+      "single_word": false,
+      "special": false
+    }
+  },
+  "bos_token": "<s>",
+  "clean_up_tokenization_spaces": true,
+  "cls_token": "<s>",
+  "eos_token": "</s>",
+  "mask_token": "<mask>",
+  "max_length": 128,
+  "model_max_length": 128,
+  "pad_token": "<pad>",
+  "sep_token": "</s>",
+  "stride": 0,
+  "tokenizer_class": "PreTrainedTokenizerFast",
+  "truncation_side": "right",
+  "truncation_strategy": "longest_first",
+  "unk_token": "<unk>"
+}

training_args.bin

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