update

README.md

@@ -1,3 +1,13 @@
 ---
 license: mit
+language:
+- en
+library_name: transformers
+pipeline_tag: text-classification
+tags:
+- transformers
+- materials
 ---
+# BatteryBERT-cased for Battery Abstract Multi-label Classification
+This model is a fine-tuned version of [BatterySciBERT-uncased model](https://huggingface.co/batterydata/batteryscibert-uncased) on a dataset of 1140 battery materials science abstracts.
+This model is uncased.

config.json

@@ -0,0 +1,40 @@
+{
+  "_name_or_path": "batteryscibert-uncased",
+  "architectures": [
+    "BertForSequenceClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "classifier_dropout": null,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "id2label": {
+    "0": "Coating",
+    "1": "Computation",
+    "2": "Doping",
+    "3": "Experiment",
+    "4": "Sodium layered oxide cathode"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "Coating": 0,
+    "Computation": 1,
+    "Doping": 2,
+    "Experiment": 3,
+    "Sodium layered oxide cathode": 4
+  },
+  "layer_norm_eps": 1e-12,
+  "max_position_embeddings": 512,
+  "model_type": "bert",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "pad_token_id": 0,
+  "position_embedding_type": "absolute",
+  "problem_type": "multi_label_classification",
+  "torch_dtype": "float32",
+  "transformers_version": "4.21.2",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 31090
+}

pytorch_model.bin

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:24728e72390ecfbd89036a03ba9a1e92ae38fb2af268b56f4bd5b5e2cd685e0b
+size 439774253

special_tokens_map.json

@@ -0,0 +1 @@
+{"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"}

tokenizer_config.json

@@ -0,0 +1 @@
+{"do_lower_case": true, "unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]", "tokenize_chinese_chars": true, "strip_accents": null, "special_tokens_map_file": null, "name_or_path": "allenai/scibert_scivocab_uncased", "do_basic_tokenize": true, "never_split": null, "tokenizer_class": "BertTokenizer"}