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-v2
+  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
+
+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: 0.4432
+- Accuracy: 0.8418
+- Precision: 0.8395
+- Recall: 0.7600
+- F1: 0.7676
+- Hamming Loss: 0.1582
+
+## 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: 1e-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 |
+|:-------------:|:-----:|:-----:|:---------------:|:--------:|:---------:|:------:|:------:|:------------:|
+| 1.4285        | 1.0   | 1744  | 1.2584          | 0.5671   | 0.6506    | 0.4372 | 0.4716 | 0.4329       |
+| 1.1788        | 2.0   | 3488  | 1.0023          | 0.6388   | 0.6753    | 0.5323 | 0.5578 | 0.3612       |
+| 0.9144        | 3.0   | 5232  | 0.7885          | 0.7093   | 0.7259    | 0.6091 | 0.6281 | 0.2907       |
+| 0.78          | 4.0   | 6976  | 0.6970          | 0.7439   | 0.7517    | 0.6527 | 0.6673 | 0.2561       |
+| 0.6565        | 5.0   | 8720  | 0.6072          | 0.7765   | 0.7792    | 0.6838 | 0.6952 | 0.2235       |
+| 0.5845        | 6.0   | 10464 | 0.5438          | 0.7995   | 0.7974    | 0.7125 | 0.7221 | 0.2005       |
+| 0.5158        | 7.0   | 12208 | 0.5127          | 0.8132   | 0.8180    | 0.7250 | 0.7362 | 0.1868       |
+| 0.4697        | 8.0   | 13952 | 0.4939          | 0.8186   | 0.8188    | 0.7345 | 0.7438 | 0.1814       |
+| 0.4251        | 9.0   | 15696 | 0.4712          | 0.8334   | 0.8349    | 0.7502 | 0.7591 | 0.1666       |
+| 0.4039        | 10.0  | 17440 | 0.4564          | 0.8381   | 0.8382    | 0.7538 | 0.7629 | 0.1619       |
+| 0.3826        | 11.0  | 19184 | 0.4479          | 0.8397   | 0.8399    | 0.7565 | 0.7656 | 0.1603       |
+| 0.3691        | 12.0  | 20928 | 0.4432          | 0.8418   | 0.8395    | 0.7600 | 0.7676 | 0.1582       |
+
+
+### 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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