End of training

README.md

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+---
+license: apache-2.0
+base_model: bert-base-multilingual-cased
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- precision
+- recall
+- f1
+model-index:
+- name: spa-eng-pos-tagging-v2.1
+  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. -->
+
+# spa-eng-pos-tagging-v2.1
+
+This model is a fine-tuned version of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1523
+- Accuracy: 0.9516
+- Precision: 0.9445
+- Recall: 0.8846
+- F1: 0.8831
+- Hamming Loss: 0.0484
+
+## 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: 3e-05
+- train_batch_size: 16
+- eval_batch_size: 32
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 14
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss | Accuracy | Precision | Recall | F1     | Hamming Loss |
+|:-------------:|:-----:|:-----:|:---------------:|:--------:|:---------:|:------:|:------:|:------------:|
+| 0.3806        | 1.0   | 1744  | 0.2730          | 0.8940   | 0.8903    | 0.8246 | 0.8252 | 0.1060       |
+| 0.2615        | 2.0   | 3488  | 0.2134          | 0.9181   | 0.9058    | 0.8514 | 0.8464 | 0.0819       |
+| 0.1864        | 3.0   | 5232  | 0.1895          | 0.9284   | 0.9224    | 0.8626 | 0.8608 | 0.0716       |
+| 0.1721        | 4.0   | 6976  | 0.1769          | 0.9352   | 0.9287    | 0.8676 | 0.8667 | 0.0648       |
+| 0.1462        | 5.0   | 8720  | 0.1840          | 0.9355   | 0.9310    | 0.8663 | 0.8670 | 0.0645       |
+| 0.1175        | 6.0   | 10464 | 0.1553          | 0.9487   | 0.9399    | 0.8820 | 0.8794 | 0.0513       |
+| 0.0949        | 7.0   | 12208 | 0.1523          | 0.9516   | 0.9445    | 0.8846 | 0.8831 | 0.0484       |
+| 0.0833        | 8.0   | 13952 | 0.1564          | 0.9535   | 0.9439    | 0.8881 | 0.8847 | 0.0465       |
+| 0.0722        | 9.0   | 15696 | 0.1566          | 0.9549   | 0.9472    | 0.8890 | 0.8867 | 0.0451       |
+| 0.0571        | 10.0  | 17440 | 0.1649          | 0.9565   | 0.9513    | 0.8875 | 0.8880 | 0.0435       |
+| 0.0516        | 11.0  | 19184 | 0.1669          | 0.9587   | 0.9523    | 0.8913 | 0.8905 | 0.0413       |
+| 0.0392        | 12.0  | 20928 | 0.1711          | 0.9598   | 0.9524    | 0.8925 | 0.8911 | 0.0402       |
+| 0.03          | 13.0  | 22672 | 0.1800          | 0.9603   | 0.9533    | 0.8935 | 0.8921 | 0.0397       |
+| 0.0308        | 14.0  | 24416 | 0.1827          | 0.9607   | 0.9537    | 0.8938 | 0.8924 | 0.0393       |
+
+
+### Framework versions
+
+- Transformers 4.32.0
+- Pytorch 2.0.1+cu118
+- Tokenizers 0.13.3

config.json

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+{
+  "_name_or_path": "bert-base-multilingual-cased",
+  "architectures": [
+    "BertForTokenClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "classifier_dropout": null,
+  "directionality": "bidi",
+  "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",
+    "7": "LABEL_7",
+    "8": "LABEL_8",
+    "9": "LABEL_9",
+    "10": "LABEL_10",
+    "11": "LABEL_11",
+    "12": "LABEL_12",
+    "13": "LABEL_13",
+    "14": "LABEL_14",
+    "15": "LABEL_15",
+    "16": "LABEL_16"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "LABEL_0": 0,
+    "LABEL_1": 1,
+    "LABEL_10": 10,
+    "LABEL_11": 11,
+    "LABEL_12": 12,
+    "LABEL_13": 13,
+    "LABEL_14": 14,
+    "LABEL_15": 15,
+    "LABEL_16": 16,
+    "LABEL_2": 2,
+    "LABEL_3": 3,
+    "LABEL_4": 4,
+    "LABEL_5": 5,
+    "LABEL_6": 6,
+    "LABEL_7": 7,
+    "LABEL_8": 8,
+    "LABEL_9": 9
+  },
+  "layer_norm_eps": 1e-12,
+  "max_position_embeddings": 512,
+  "model_type": "bert",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "pad_token_id": 0,
+  "pooler_fc_size": 768,
+  "pooler_num_attention_heads": 12,
+  "pooler_num_fc_layers": 3,
+  "pooler_size_per_head": 128,
+  "pooler_type": "first_token_transform",
+  "position_embedding_type": "absolute",
+  "torch_dtype": "float32",
+  "transformers_version": "4.32.0",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 119547
+}

pytorch_model.bin

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training_args.bin

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