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README.md

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+---
+language:
+- en
+- de
+license: apache-2.0
+library_name: transformers
+datasets:
+- FreedomIntelligence/sharegpt-deutsch
+- mayflowergmbh/oasst_de
+- mayflowergmbh/dolly_15k_de
+- mayflowergmbh/openschnabeltier_de
+- mayflowergmbh/ultrachat_de
+- WizardLM/WizardLM_evol_instruct_V2_196k
+- mayflowergmbh/evol_instruct_de
+- mayflowergmbh/alpaca-gpt4_de
+- mayflowergmbh/dolphin_de
+- mayflowergmbh/airoboros_de
+pipeline-tag: text-generation
+model-index:
+- name: ende-chat-0.0.7
+  results: []
+---
+
+
+# Model Card for EnDe-chat-0.0.7
+
+Preliminary LoRA finetune of Mistral-7B for German and English quality text.
+
+This version has an **extended tokenizer**, to make the model able to handle longer input.
+
+This is an experiment to improve the German capabilities of Mistral with
+continued finetuning. The finetuning also includes English data, in order to
+retain the English capabilities, to allow the model to be used for translation
+and for answering German questions on English documents and vice versa.
+
+Unfortunately, the compute available for this experiment (2xV100) was not at
+all sufficient for the amount of training data we would have liked to include.
+
+After continued pretraining, this model has received instruction finetuning.
+
+#  Table of Contents
+
+- [Model Details](#model-details)
+  - [Model Description](#model-description)
+- [Uses](#uses)
+  - [Out-of-Scope Use](#out-of-scope-use)
+- [Bias, Risks, and Limitations](#bias-risks-and-limitations)
+  - [Recommendations](#recommendations)
+- [Training Details](#training-details)
+  - [Training Data](#training-data)
+  - [Training Procedure](#training-procedure)
+- [Evaluation](#evaluation)
+- [Examples](#examples)
+
+
+# Model Details
+
+## Model Description
+
+LoRA finetune of Mistral-7B for German and English quality text.
+
+- **Developed by:** Erich Schubert
+- **Model type:** Language model
+- **Language(s) (NLP):** deu, eng
+- **License:** apache-2.0
+- **Parent Model:** mistralai/Mistral-7B-v0.1
+- **Resources for more information:** n/a
+
+
+# Uses
+
+Model finetuned for chat in German and English.
+
+## Out-of-Scope Use
+
+The model has not received alignment or instruction finetuning, this is intended as a chat foundation model.
+
+
+# Bias, Risks, and Limitations
+
+Significant research has explored bias and fairness issues with language models (see, e.g., [Sheng et al. (2021)](https://aclanthology.org/2021.acl-long.330.pdf) and [Bender et al. (2021)](https://dl.acm.org/doi/pdf/10.1145/3442188.3445922)). Predictions generated by the model may include disturbing and harmful stereotypes across protected classes; identity characteristics; and sensitive, social, and occupational groups.
+
+
+## Recommendations
+
+Further finetuning necessary!
+
+
+# Training Details
+
+## Training Data
+
+Pretrained on proprietary text collected from the internet, with a focus on
+quality German and English text.
+
+Typical benchmarking data should not be present in this data set.
+
+This is no longer as clear for the finetuning data sets, but the
+amount of data and compute for instruction tuning was much less.
+
+
+## Training Procedure
+
+Initial LoRA finetuning with LLaMA-Factory using a mixture of **English and
+German** data, with a focus on data quality.
+
+Unfortunately, I could use 100x as much GPU power as I had available for this
+experiment, and had to heavily subsample the data. As is, this is largely a
+proof of concept to see if we can improve model quality with better data.
+
+This version then received basic chat/instruction training with
+```
+    --stage sft \
+    --model_name_or_path ende-0.0.7 \
+    --finetuning_type lora \
+    --template default \
+    --dataset_dir data \
+    --dataset sharegpt-deutsch,oasst_de,dolly_15k_de,openschnabeltier_de,ultrachat_de,evol_instruct,evol_instruct_de,alpaca-gpt4_de,dolphin_de,airoboros_de \
+    --cutoff_len 1024 \
+    --learning_rate 5e-05 \
+    --num_train_epochs 1.0 \
+    --per_device_train_batch_size 4 \
+    --gradient_accumulation_steps 8 \
+    --lr_scheduler_type cosine \
+    --neftune_noise_alpha 0 \
+    --lora_target all \
+    --lora_rank 8 \
+    --lora_dropout 0 \
+    --fp16 True \
+```
+
+Unfortunately, **most of this fine-tuning data is just automatically
+translated from English**. I do not think this leads to particularly
+high-quality data.
+
+# Evaluation
+
+Not fully evaluated, as it has not been completely trained.
+
+Also, I believe that our **benchmarks tend to be misleading**.
+In particular the huggingface leaderboard is flooded with overfitted models
+with little to no value. Real-world performance may be task specific and
+needs to be evaluated carefully on a case basis. I hope some will find
+this model to be useful!
+
+**You are welcome to contribute evaluation scores!**
+

config.json

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+{
+  "_name_or_path": "ende-0.0.7",
+  "architectures": [
+    "MistralForCausalLM"
+  ],
+  "attention_dropout": 0.0,
+  "bos_token_id": 1,
+  "eos_token_id": 2,
+  "hidden_act": "silu",
+  "hidden_size": 4096,
+  "initializer_range": 0.02,
+  "intermediate_size": 14336,
+  "max_position_embeddings": 32768,
+  "model_type": "mistral",
+  "num_attention_heads": 32,
+  "num_hidden_layers": 32,
+  "num_key_value_heads": 8,
+  "rms_norm_eps": 1e-05,
+  "rope_theta": 10000.0,
+  "sliding_window": 4096,
+  "tie_word_embeddings": false,
+  "torch_dtype": "float16",
+  "transformers_version": "4.41.2",
+  "use_cache": true,
+  "vocab_size": 111235
+}

generation_config.json

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+{
+  "_from_model_config": true,
+  "bos_token_id": 1,
+  "eos_token_id": 2,
+  "transformers_version": "4.41.2"
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special_tokens_map.json

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+{
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+    "content": "<s>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
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+    "content": "</s>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "pad_token": {
+    "content": "</s>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "unk_token": {
+    "content": "<unk>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  }
+}

tokenizer_config.json

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+{
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+      "single_word": false,
+      "special": true
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+      "single_word": false,
+      "special": true
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+  "bos_token": "<s>",
+  "chat_template": "{% if messages[0]['role'] == 'system' %}{% set system_message = messages[0]['content'] %}{% endif %}{% if system_message is defined %}{{ system_message + '\n' }}{% endif %}{% for message in messages %}{% set content = message['content'] %}{% if message['role'] == 'user' %}{{ 'Human: ' + content + '\nAssistant: ' }}{% elif message['role'] == 'assistant' %}{{ content + '</s>' + '\n' }}{% endif %}{% endfor %}",
+  "clean_up_tokenization_spaces": false,
+  "eos_token": "</s>",
+  "legacy": true,
+  "model_max_length": 1000000000000000019884624838656,
+  "pad_token": "</s>",
+  "padding_side": "left",
+  "split_special_tokens": false,
+  "tokenizer_class": "LlamaTokenizerFast",
+  "unk_token": "<unk>",
+  "use_default_system_prompt": false
+}