End of training

README.md

@@ -1,43 +1,67 @@
 ---
-license: apache-2.0
+base_model: damienbenveniste/mistral-supervised
+library_name: transformers
+model_name: mistral-ppo
 tags:
-- trl
+- generated_from_trainer
 - ppo
-- transformers
-- reinforcement-learning
+- trl
+licence: license
 ---
 
-# TRL Model
+# Model Card for mistral-ppo
 
-This is a [TRL language model](https://github.com/huggingface/trl) that has been fine-tuned with reinforcement learning to
- guide the model outputs according to a value, function, or human feedback. The model can be used for text generation.
+This model is a fine-tuned version of [damienbenveniste/mistral-supervised](https://huggingface.co/damienbenveniste/mistral-supervised).
+It has been trained using [TRL](https://github.com/huggingface/trl).
 
-## Usage
+## Quick start
 
-To use this model for inference, first install the TRL library:
+```python
+from transformers import pipeline
 
-```bash
-python -m pip install trl
+question = "If you had a time machine, but could only go to the past or the future once and never return, which would you choose and why?"
+generator = pipeline("text-generation", model="damienbenveniste/mistral-ppo", device="cuda")
+output = generator([{"role": "user", "content": question}], max_new_tokens=128, return_full_text=False)[0]
+print(output["generated_text"])
 ```
 
-You can then generate text as follows:
+## Training procedure
 
-```python
-from transformers import pipeline
+ 
 
-generator = pipeline("text-generation", model="damienbenveniste//private/var/folders/dy/k5ycdcns28s2cxl8hc76v2mr0000gn/T/tmpl2a_v6sk/damienbenveniste/mistral-ppo")
-outputs = generator("Hello, my llama is cute")
-```
 
-If you want to use the model for training or to obtain the outputs from the value head, load the model as follows:
+This model was trained with PPO, a method introduced in [Fine-Tuning Language Models from Human Preferences](https://huggingface.co/papers/1909.08593).
 
-```python
-from transformers import AutoTokenizer
-from trl import AutoModelForCausalLMWithValueHead
+### Framework versions
+
+- TRL: 0.19.1
+- Transformers: 4.52.4
+- Pytorch: 2.7.0
+- Datasets: 3.6.0
+- Tokenizers: 0.21.1
 
-tokenizer = AutoTokenizer.from_pretrained("damienbenveniste//private/var/folders/dy/k5ycdcns28s2cxl8hc76v2mr0000gn/T/tmpl2a_v6sk/damienbenveniste/mistral-ppo")
-model = AutoModelForCausalLMWithValueHead.from_pretrained("damienbenveniste//private/var/folders/dy/k5ycdcns28s2cxl8hc76v2mr0000gn/T/tmpl2a_v6sk/damienbenveniste/mistral-ppo")
+## Citations
 
-inputs = tokenizer("Hello, my llama is cute", return_tensors="pt")
-outputs = model(**inputs, labels=inputs["input_ids"])
+Cite PPO as:
+
+```bibtex
+@article{mziegler2019fine-tuning,
+    title        = {{Fine-Tuning Language Models from Human Preferences}},
+    author       = {Daniel M. Ziegler and Nisan Stiennon and Jeffrey Wu and Tom B. Brown and Alec Radford and Dario Amodei and Paul F. Christiano and Geoffrey Irving},
+    year         = 2019,
+    eprint       = {arXiv:1909.08593}
+}
 ```
+
+Cite TRL as:
+    
+```bibtex
+@misc{vonwerra2022trl,
+	title        = {{TRL: Transformer Reinforcement Learning}},
+	author       = {Leandro von Werra and Younes Belkada and Lewis Tunstall and Edward Beeching and Tristan Thrush and Nathan Lambert and Shengyi Huang and Kashif Rasul and Quentin Gallou{\'e}dec},
+	year         = 2020,
+	journal      = {GitHub repository},
+	publisher    = {GitHub},
+	howpublished = {\url{https://github.com/huggingface/trl}}
+}
+```

chat_template.jinja

@@ -0,0 +1,89 @@
+{%- if tools %}
+    {{- '<|im_start|>system\n' }}
+    {%- if messages[0].role == 'system' %}
+        {{- messages[0].content + '\n\n' }}
+    {%- endif %}
+    {{- "# Tools\n\nYou may call one or more functions to assist with the user query.\n\nYou are provided with function signatures within <tools></tools> XML tags:\n<tools>" }}
+    {%- for tool in tools %}
+        {{- "\n" }}
+        {{- tool | tojson }}
+    {%- endfor %}
+    {{- "\n</tools>\n\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\n<tool_call>\n{\"name\": <function-name>, \"arguments\": <args-json-object>}\n</tool_call><|im_end|>\n" }}
+{%- else %}
+    {%- if messages[0].role == 'system' %}
+        {{- '<|im_start|>system\n' + messages[0].content + '<|im_end|>\n' }}
+    {%- endif %}
+{%- endif %}
+{%- set ns = namespace(multi_step_tool=true, last_query_index=messages|length - 1) %}
+{%- for message in messages[::-1] %}
+    {%- set index = (messages|length - 1) - loop.index0 %}
+    {%- if ns.multi_step_tool and message.role == "user" and message.content is string and not(message.content.startswith('<tool_response>') and message.content.endswith('</tool_response>')) %}
+        {%- set ns.multi_step_tool = false %}
+        {%- set ns.last_query_index = index %}
+    {%- endif %}
+{%- endfor %}
+{%- for message in messages %}
+    {%- if message.content is string %}
+        {%- set content = message.content %}
+    {%- else %}
+        {%- set content = '' %}
+    {%- endif %}
+    {%- if (message.role == "user") or (message.role == "system" and not loop.first) %}
+        {{- '<|im_start|>' + message.role + '\n' + content + '<|im_end|>' + '\n' }}
+    {%- elif message.role == "assistant" %}
+        {%- set reasoning_content = '' %}
+        {%- if message.reasoning_content is string %}
+            {%- set reasoning_content = message.reasoning_content %}
+        {%- else %}
+            {%- if '</think>' in content %}
+                {%- set reasoning_content = content.split('</think>')[0].rstrip('\n').split('<think>')[-1].lstrip('\n') %}
+                {%- set content = content.split('</think>')[-1].lstrip('\n') %}
+            {%- endif %}
+        {%- endif %}
+        {%- if loop.index0 > ns.last_query_index %}
+            {%- if loop.last or (not loop.last and reasoning_content) %}
+                {{- '<|im_start|>' + message.role + '\n<think>\n' + reasoning_content.strip('\n') + '\n</think>\n\n' + content.lstrip('\n') }}
+            {%- else %}
+                {{- '<|im_start|>' + message.role + '\n' + content }}
+            {%- endif %}
+        {%- else %}
+            {{- '<|im_start|>' + message.role + '\n' + content }}
+        {%- endif %}
+        {%- if message.tool_calls %}
+            {%- for tool_call in message.tool_calls %}
+                {%- if (loop.first and content) or (not loop.first) %}
+                    {{- '\n' }}
+                {%- endif %}
+                {%- if tool_call.function %}
+                    {%- set tool_call = tool_call.function %}
+                {%- endif %}
+                {{- '<tool_call>\n{"name": "' }}
+                {{- tool_call.name }}
+                {{- '", "arguments": ' }}
+                {%- if tool_call.arguments is string %}
+                    {{- tool_call.arguments }}
+                {%- else %}
+                    {{- tool_call.arguments | tojson }}
+                {%- endif %}
+                {{- '}\n</tool_call>' }}
+            {%- endfor %}
+        {%- endif %}
+        {{- '<|im_end|>\n' }}
+    {%- elif message.role == "tool" %}
+        {%- if loop.first or (messages[loop.index0 - 1].role != "tool") %}
+            {{- '<|im_start|>user' }}
+        {%- endif %}
+        {{- '\n<tool_response>\n' }}
+        {{- content }}
+        {{- '\n</tool_response>' }}
+        {%- if loop.last or (messages[loop.index0 + 1].role != "tool") %}
+            {{- '<|im_end|>\n' }}
+        {%- endif %}
+    {%- endif %}
+{%- endfor %}
+{%- if add_generation_prompt %}
+    {{- '<|im_start|>assistant\n' }}
+    {%- if enable_thinking is defined and enable_thinking is false %}
+        {{- '<think>\n\n</think>\n\n' }}
+    {%- endif %}
+{%- endif %}

config.json

@@ -1,12 +1,11 @@
 {
-  "_name_or_path": "damienbenveniste/mistral-supervised",
   "architectures": [
     "MistralForCausalLM"
   ],
   "attention_dropout": 0.0,
   "bos_token_id": 1,
-  "eos_token_id": 2,
-  "head_dim": 48,
+  "eos_token_id": 32002,
+  "head_dim": null,
   "hidden_act": "silu",
   "hidden_size": 768,
   "initializer_range": 0.02,
@@ -16,12 +15,13 @@
   "num_attention_heads": 16,
   "num_hidden_layers": 4,
   "num_key_value_heads": 8,
+  "pad_token_id": 2,
   "rms_norm_eps": 1e-06,
   "rope_theta": 10000.0,
   "sliding_window": 768,
   "tie_word_embeddings": false,
   "torch_dtype": "float32",
-  "transformers_version": "4.44.2",
+  "transformers_version": "4.52.4",
   "use_cache": true,
-  "vocab_size": 32000
+  "vocab_size": 32064
 }

generation_config.json

@@ -1,6 +1,5 @@
 {
   "_from_model_config": true,
   "bos_token_id": 1,
-  "eos_token_id": 2,
-  "transformers_version": "4.44.2"
+  "transformers_version": "4.52.4"
 }

model.safetensors

@@ -1,3 +1,3 @@
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-oid sha256:85ee50a22dabf1652e2365843c33fbb25cab5fa12acf25bc0c36147211f49b65
-size 338200972
+oid sha256:d7942f5514948f01ae97d037aeea8f918367c1c9fb12e4f747d69cb0af3ccddd
+size 338590928

special_tokens_map.json

@@ -6,13 +6,7 @@
     "rstrip": false,
     "single_word": false
   },
-  "eos_token": {
-    "content": "</s>",
-    "lstrip": false,
-    "normalized": false,
-    "rstrip": false,
-    "single_word": false
-  },
+  "eos_token": "<|im_end|>",
   "pad_token": {
     "content": "</s>",
     "lstrip": false,

tokenizer_config.json

@@ -26,12 +26,221 @@
       "rstrip": false,
       "single_word": false,
       "special": true
+    },
+    "32000": {
+      "content": "<|endoftext|>",
+      "lstrip": false,
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+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "32001": {
+      "content": "<|im_start|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "32002": {
+      "content": "<|im_end|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "32003": {
+      "content": "<|object_ref_start|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "32004": {
+      "content": "<|object_ref_end|>",
+      "lstrip": false,
+      "normalized": false,
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+      "special": true
+    },
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+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
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+      "special": true
+    },
+    "32006": {
+      "content": "<|box_end|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
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+    },
+    "32007": {
+      "content": "<|quad_start|>",
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+      "special": false
+    },
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+      "content": "<|fim_middle|>",
+      "lstrip": false,
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+      "content": "<|repo_name|>",
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+    "32023": {
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+    "32024": {
+      "content": "<think>",
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+    "32025": {
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     }
   },
   "additional_special_tokens": [],
   "bos_token": "<s>",
   "clean_up_tokenization_spaces": false,
-  "eos_token": "</s>",
+  "eos_token": "<|im_end|>",
+  "extra_special_tokens": {},
   "legacy": false,
   "max_length": 512,
   "model_max_length": 1000000000000000019884624838656,

training_args.bin

@@ -0,0 +1,3 @@
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+oid sha256:383131c08d83084076f852ac7a30176581b7c578685bc7e6ae8ad17b29c03fdb
+size 6545