End of training

README.md

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+---
+license: apache-2.0
+base_model: distilbert-base-multilingual-cased
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- precision
+- recall
+- f1
+model-index:
+- name: spa-eng-pos-tagging-v4
+  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-v4
+
+This model is a fine-tuned version of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.3366
+- Accuracy: 0.9071
+- Precision: 0.9038
+- Recall: 0.8314
+- F1: 0.8361
+- Hamming Loss: 0.0929
+
+## 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: 12
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss | Accuracy | Precision | Recall | F1     | Hamming Loss |
+|:-------------:|:-----:|:-----:|:---------------:|:--------:|:---------:|:------:|:------:|:------------:|
+| 1.1797        | 1.0   | 1744  | 0.9547          | 0.6615   | 0.6780    | 0.5703 | 0.5810 | 0.3385       |
+| 0.7267        | 2.0   | 3488  | 0.5924          | 0.7785   | 0.7766    | 0.6921 | 0.7005 | 0.2215       |
+| 0.5048        | 3.0   | 5232  | 0.4816          | 0.8272   | 0.8107    | 0.7596 | 0.7526 | 0.1728       |
+| 0.4095        | 4.0   | 6976  | 0.4585          | 0.8331   | 0.8289    | 0.7549 | 0.7587 | 0.1669       |
+| 0.3369        | 5.0   | 8720  | 0.3830          | 0.8648   | 0.8621    | 0.7904 | 0.7940 | 0.1352       |
+| 0.2888        | 6.0   | 10464 | 0.3506          | 0.8793   | 0.8715    | 0.8074 | 0.8077 | 0.1207       |
+| 0.2397        | 7.0   | 12208 | 0.3485          | 0.8848   | 0.8845    | 0.8077 | 0.8143 | 0.1152       |
+| 0.2093        | 8.0   | 13952 | 0.3523          | 0.8891   | 0.8864    | 0.8156 | 0.8190 | 0.1109       |
+| 0.1723        | 9.0   | 15696 | 0.3538          | 0.8912   | 0.8931    | 0.8143 | 0.8217 | 0.1088       |
+| 0.1558        | 10.0  | 17440 | 0.3436          | 0.8997   | 0.8958    | 0.8252 | 0.8290 | 0.1003       |
+| 0.1344        | 11.0  | 19184 | 0.3373          | 0.9053   | 0.9013    | 0.8302 | 0.8343 | 0.0947       |
+| 0.1134        | 12.0  | 20928 | 0.3366          | 0.9071   | 0.9038    | 0.8314 | 0.8361 | 0.0929       |
+
+
+### Framework versions
+
+- Transformers 4.32.0
+- Pytorch 2.0.1+cu118
+- Tokenizers 0.13.3

config.json

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+{
+  "_name_or_path": "distilbert-base-multilingual-cased",
+  "activation": "gelu",
+  "architectures": [
+    "BertForTokenClassification"
+  ],
+  "attention_dropout": 0.1,
+  "attention_probs_dropout_prob": 0.1,
+  "classifier_dropout": null,
+  "dim": 768,
+  "dropout": 0.1,
+  "hidden_act": "gelu",
+  "hidden_dim": 3072,
+  "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",
+  "n_heads": 12,
+  "n_layers": 6,
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "output_past": true,
+  "pad_token_id": 0,
+  "position_embedding_type": "absolute",
+  "qa_dropout": 0.1,
+  "seq_classif_dropout": 0.2,
+  "sinusoidal_pos_embds": false,
+  "tie_weights_": true,
+  "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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