End of training

README.md

@@ -1,74 +1,74 @@
----
-base_model: daveni/twitter-xlm-roberta-emotion-es
-tags:
-- generated_from_trainer
-metrics:
-- accuracy
-- f1
-- precision
-- recall
-model-index:
-- name: base
-  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. -->
-
-# base
-
-This model is a fine-tuned version of [daveni/twitter-xlm-roberta-emotion-es](https://huggingface.co/daveni/twitter-xlm-roberta-emotion-es) on an unknown dataset.
-It achieves the following results on the evaluation set:
-- Loss: 0.9425
-- Accuracy: 0.8465
-- F1: 0.8
-- Precision: 0.8667
-- Recall: 0.7429
-
-## 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: 16
-- eval_batch_size: 8
-- 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 | F1     | Precision | Recall |
-|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
-| 0.6431        | 1.0   | 64   | 0.5474          | 0.7362   | 0.6171 | 0.7714    | 0.5143 |
-| 0.4576        | 2.0   | 128  | 0.5103          | 0.7795   | 0.7358 | 0.7290    | 0.7429 |
-| 0.2933        | 3.0   | 192  | 0.5647          | 0.8228   | 0.7619 | 0.8571    | 0.6857 |
-| 0.198         | 4.0   | 256  | 0.6377          | 0.8346   | 0.7742 | 0.8889    | 0.6857 |
-| 0.113         | 5.0   | 320  | 0.6867          | 0.8504   | 0.7935 | 0.9241    | 0.6952 |
-| 0.057         | 6.0   | 384  | 0.8875          | 0.8189   | 0.7788 | 0.7864    | 0.7714 |
-| 0.0282        | 7.0   | 448  | 0.9361          | 0.8346   | 0.7879 | 0.8387    | 0.7429 |
-| 0.0234        | 8.0   | 512  | 1.0229          | 0.8228   | 0.7826 | 0.7941    | 0.7714 |
-| 0.0095        | 9.0   | 576  | 0.9131          | 0.8622   | 0.8168 | 0.9070    | 0.7429 |
-| 0.0101        | 10.0  | 640  | 0.9425          | 0.8465   | 0.8    | 0.8667    | 0.7429 |
-
-
-### Framework versions
-
-- Transformers 4.43.0.dev0
-- Pytorch 2.0.1+cu117
-- Datasets 2.19.1
-- Tokenizers 0.19.1
+---
+base_model: daveni/twitter-xlm-roberta-emotion-es
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- f1
+- precision
+- recall
+model-index:
+- name: base
+  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. -->
+
+# base
+
+This model is a fine-tuned version of [daveni/twitter-xlm-roberta-emotion-es](https://huggingface.co/daveni/twitter-xlm-roberta-emotion-es) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.1501
+- Accuracy: 0.8346
+- F1: 0.7717
+- Precision: 0.8987
+- Recall: 0.6762
+
+## 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: 32
+- eval_batch_size: 16
+- 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 | F1     | Precision | Recall |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
+| 0.6694        | 1.0   | 32   | 0.6008          | 0.6969   | 0.4901 | 0.8043    | 0.3524 |
+| 0.5305        | 2.0   | 64   | 0.4786          | 0.7795   | 0.6854 | 0.8356    | 0.5810 |
+| 0.3457        | 3.0   | 96   | 0.4456          | 0.8031   | 0.7788 | 0.7273    | 0.8381 |
+| 0.2513        | 4.0   | 128  | 0.5167          | 0.8307   | 0.7725 | 0.8690    | 0.6952 |
+| 0.1725        | 5.0   | 160  | 0.6917          | 0.8189   | 0.7604 | 0.8391    | 0.6952 |
+| 0.0974        | 6.0   | 192  | 0.7955          | 0.8228   | 0.7619 | 0.8571    | 0.6857 |
+| 0.042         | 7.0   | 224  | 0.8829          | 0.8346   | 0.7766 | 0.8795    | 0.6952 |
+| 0.014         | 8.0   | 256  | 0.9991          | 0.8189   | 0.7653 | 0.8242    | 0.7143 |
+| 0.0103        | 9.0   | 288  | 1.1313          | 0.8346   | 0.7717 | 0.8987    | 0.6762 |
+| 0.0194        | 10.0  | 320  | 1.1501          | 0.8346   | 0.7717 | 0.8987    | 0.6762 |
+
+
+### Framework versions
+
+- Transformers 4.43.3
+- Pytorch 2.4.0
+- Datasets 2.20.0
+- Tokenizers 0.19.1

config.json

@@ -1,38 +1,38 @@
-{
-  "_name_or_path": "daveni/twitter-xlm-roberta-emotion-es",
-  "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": "POSITIVE"
-  },
-  "initializer_range": 0.02,
-  "intermediate_size": 3072,
-  "label2id": {
-    "NEGATIVE": 0,
-    "POSITIVE": 1
-  },
-  "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": "4.43.0.dev0",
-  "type_vocab_size": 1,
-  "use_cache": true,
-  "vocab_size": 250002
-}
+{
+  "_name_or_path": "daveni/twitter-xlm-roberta-emotion-es",
+  "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": "POSITIVE"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "NEGATIVE": 0,
+    "POSITIVE": 1
+  },
+  "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": "4.43.3",
+  "type_vocab_size": 1,
+  "use_cache": true,
+  "vocab_size": 250002
+}

model.safetensors

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special_tokens_map.json

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-{
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+  }
+}

tokenizer_config.json

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-{
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-  "model_max_length": 1000000000000000019884624838656,
-  "pad_token": "<pad>",
-  "sep_token": "</s>",
-  "tokenizer_class": "XLMRobertaTokenizer",
-  "unk_token": "<unk>"
-}
+{
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+  "bos_token": "<s>",
+  "clean_up_tokenization_spaces": true,
+  "cls_token": "<s>",
+  "eos_token": "</s>",
+  "mask_token": "<mask>",
+  "model_max_length": 1000000000000000019884624838656,
+  "pad_token": "<pad>",
+  "sep_token": "</s>",
+  "tokenizer_class": "XLMRobertaTokenizer",
+  "unk_token": "<unk>"
+}

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