lBober/my-model-SaBERT-Area

README.md

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+---
+license: apache-2.0
+base_model: VerificadoProfesional/SaBERT-Spanish-Sentiment-Analysis
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: my-model-SaBERT-Area
+  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. -->
+
+# my-model-SaBERT-Area
+
+This model is a fine-tuned version of [VerificadoProfesional/SaBERT-Spanish-Sentiment-Analysis](https://huggingface.co/VerificadoProfesional/SaBERT-Spanish-Sentiment-Analysis) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.5236
+- Accuracy: 0.4173
+
+## 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: 100
+- eval_batch_size: 100
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 10
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 1.8312        | 1.0   | 7    | 1.7417          | 0.3022   |
+| 1.6365        | 2.0   | 14   | 1.6915          | 0.3165   |
+| 1.5135        | 3.0   | 21   | 1.6488          | 0.3525   |
+| 1.3915        | 4.0   | 28   | 1.6102          | 0.3525   |
+| 1.2707        | 5.0   | 35   | 1.5685          | 0.4173   |
+| 1.1772        | 6.0   | 42   | 1.5384          | 0.4388   |
+| 1.0696        | 7.0   | 49   | 1.5229          | 0.4245   |
+| 0.9962        | 8.0   | 56   | 1.5187          | 0.4173   |
+| 0.9411        | 9.0   | 63   | 1.5232          | 0.4317   |
+| 0.9334        | 10.0  | 70   | 1.5236          | 0.4173   |
+
+
+### Framework versions
+
+- Transformers 4.41.0
+- Pytorch 2.3.0+cu121
+- Datasets 2.19.1
+- Tokenizers 0.19.1

config.json

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+{
+  "_name_or_path": "VerificadoProfesional/SaBERT-Spanish-Sentiment-Analysis",
+  "architectures": [
+    "BertForSequenceClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "classifier_dropout": null,
+  "gradient_checkpointing": false,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "id2label": {
+    "0": "LABEL_0",
+    "1": "LABEL_1",
+    "2": "LABEL_2",
+    "3": "LABEL_3",
+    "4": "LABEL_4",
+    "5": "LABEL_5",
+    "6": "LABEL_6"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "LABEL_0": 0,
+    "LABEL_1": 1,
+    "LABEL_2": 2,
+    "LABEL_3": 3,
+    "LABEL_4": 4,
+    "LABEL_5": 5,
+    "LABEL_6": 6
+  },
+  "layer_norm_eps": 1e-12,
+  "max_position_embeddings": 512,
+  "model_type": "bert",
+  "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": "4.41.0",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 31002
+}

model.safetensors

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+size 439448588

runs/May25_10-17-19_883a8495c7ab/events.out.tfevents.1716632242.883a8495c7ab.1107.0

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training_args.bin

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